{
    "domain": "messages",
    "locale_data": {
        "messages": {
            "1": [
                "1"
            ],
            "": {
                "domain": "messages",
                "plural_forms": "nplurals=2; plural=n != 1;",
                "lang": "nl"
            },
            "'{col}' contains infinite values": [
                "'{col}' bevat waarden die oneindig zijn"
            ],
            "'{col}' contains missing values": [
                "'{col}' bevat ontbrekende waarden"
            ],
            "'{col}' contains only missing values": [
                "'{col}' bevat uitsluitend ontbrekende waarden"
            ],
            "'{col}' contains only one unique value": [
                "'{col}' bevat slechts één unieke waarde"
            ],
            "'{method}' extraction method was used in combination with a '{rotation}' rotation": [
                "Extractiemethode '{method}' is gebruikt in combinatie met rotatie '{rotation}'"
            ],
            "'{rotation}' rotation was used": [
                "Rotatie '{rotation}' is gebruikt"
            ],
            "'{var}' contains negative values. Negative weights are not permitted.": [
                "'{var}' bevat negatieve waarden. Negatieve gewichten zijn niet toegestaan."
            ],
            "{} - Kendall's Tau B": [
                "{} - Kendalls tau B"
            ],
            "{} - Pearson's r": [
                "{} - Pearsons r"
            ],
            "{} - Spearman's rho": [
                "{} - Spearmans rho"
            ],
            "{ciWidth}% CI Lower": [
                "{ciWidth}% ondergrens betrouwbaarheidsinterval"
            ],
            "{ciWidth}% CI mean {title}": [
                "{ciWidth}% gemiddelde betrouwbaarheidsinterval {title}"
            ],
            "{ciWidth}% CI Upper": [
                "{ciWidth}% bovengrens betrouwbaarheidsinterval"
            ],
            "{ciWidth}% Confidence Interval": [
                "{ciWidth}% betrouwbaarheidsinterval"
            ],
            "{ciWidth}% Confidence Intervals": [
                "{ciWidth}% betrouwbaarheidsintervallen"
            ],
            "{item1} and {item2}": [
                "{item1} en {item2}"
            ],
            "{list}, {nextItem}": [
                "{list}, {nextItem}"
            ],
            "{list}, and {lastItem}": [
                "{list} en {lastItem}"
            ],
            "{n} pair(s) of values were tied": [
                "{n} waardepaar/-paren verbonden"
            ],
            "{type} score based on the variables {vars}": [
                "{type}-score gebaseerd op variabelen {vars}"
            ],
            "{varName} (reversed)": [
                "{varName} (omgekeerd)"
            ],
            "{varType} of binomial logistic regression model{modelNo}": [
                "{varType} van binomiaal logistisch regressiemodel{modelNo}"
            ],
            "{varType} of linear regression model{modelNo}": [
                "{varType} van lineair regressiemodel{modelNo}"
            ],
            "* p < .05, ** p < .01, *** p < .001, one-tailed": [
                "* p < .05, ** p < .01, *** p < .001, eenzijdig"
            ],
            "%": [
                "%"
            ],
            "% Correct": [
                "% juist"
            ],
            "% of Total": [
                "% van totaal"
            ],
            "% of total": [
                "% van totaal"
            ],
            "% of Variance": [
                "% van variantie"
            ],
            "% within column": [
                "% binnen kolom"
            ],
            "% within row": [
                "% binnen rij"
            ],
            "`'1'`, `'2'` or `'3'` (default), the sum of squares to use": [
                "`'1'`, `'2'` of `'3'` (standaard); de som van de te gebruiken vierkantswortels"
            ],
            "`'2'` or `'3'` (default), the sum of squares to use": [
                "`'2'` of `'3'` (standaard); de te gebruiken kwadratensom"
            ],
            "`'different'` (default), `'oneGreater'` or `'twoGreater'`, the alternative hypothesis; group 1 different to group 2, group 1 greater than group 2, and group 2 greater than group 1 respectively": [
                "`'different'` (standaard), `'oneGreater'` of `'twoGreater'`; de alternatieve hypothese, respectievelijk: groep 1 ongelijk aan groep 2, groep 1 groter dan groep 2, groep 2 groter dan groep 1"
            ],
            "`'different'` (default), `'oneGreater'` or `'twoGreater'`, the alternative hypothesis; measure 1 different to measure 2, measure 1 greater than measure 2, and measure 2 greater than measure 1 respectively": [
                "`'different'` (standaard), `'oneGreater'` of `'twoGreater'`; de alternatieve hypothese, resp.: meting 1 verschilt aan meting 2, meting 1 groter dan meting 2, meting 2 groter dan meting 1"
            ],
            "`'dt'` (default), `'gt'` or `'lt'`, the alternative hypothesis; different to `testValue`, greater than `testValue`, and less than `testValue` respectively": [
                "`'dt'` (standaard), `'gr'` of `'lt'`; de alternatieve hypothese, resp.: verschilt aan `testValue`, groter dan `testValue`, minder dan `testValue`"
            ],
            "`'facVar'` or `'facInd'`, how to contrain the model; `'facVar'` fixes the factor variances to one, `'facInd'` fixes each factor to the scale of its first indicator.": [
                ""
            ],
            "`'listwise'` or `'fiml'`, how to handle missing values; `'listwise'` excludes a row from all analyses if one of its entries is missing, `'fiml'` uses a full information maximum likelihood method to estimate the model.": [
                "`'listwise'` of `'fiml'`, hoe er met ontbrekende waarden omgegaan wordt; `'listwise'` sluit de hele rij uit van alle analyses als de rij een ontbrekende waarde bevat, `'fiml'` gebruikt een full-information-maximum-likelihoodmethode om het model te schatten."
            ],
            "`'means'` (default) or `'medians'`, the error bars to use in the plot": [
                "`'means'` (standaard) of `'medians'`, de foutbalken om in de figuur te gebruiken"
            ],
            "`'minres'` (default), `'ml'`, or `'pa'` use respectively 'minimum residual', 'maximum likelihood', or 'prinicipal axis' as the factor extraction method": [
                "`'minres'` (standaard), `'ml'`, of `'pa'` gebruiken respectievelijk 'minimumresidu', 'maximumwaarschijnlijkheid', of 'hoofdas' als factorextractiemethode"
            ],
            "`'none'`, `'ci'` (default), or `'se'`. Use no error bars, use confidence intervals, or use standard errors on the marginal mean plots, respectively": [
                "`'none'`, `'ci'` (standaard) of `'se'`. Gebruik resp. geen foutbalken, betrouwbaarheidsintervallen of standaardfouten op de grafieken met marginale gemiddelden"
            ],
            "`'none'`, `'gamesHowell'` or `'tukey'`, which post-hoc tests to provide; `'none'` shows no post-hoc tests, `'gamesHowell'` shows Games-Howell post-hoc tests where no equivalence of variances is assumed, and `'tukey'` shows Tukey post-hoc tests where equivalence of variances is assumed": [
                "`'none'`, `'gamesHowell'` of `'tukey'`, welke post-hoctoets zal worden berekend; `'none'` toont geen post-hoctoetsen, `'gamesHowell'` toont post-hoctoetsen van Games-Howell waarbij geen variantie-equivalentie aangenomen wordt en `'tukey'` toont post-hoctoetsen waarbij variantie-equivalentie wel wordt aangenomen"
            ],
            "`'none'`, `'varimax'` (default), `'quartimax'`, `'promax'`, `'oblimin'`, or `'simplimax'`, the rotation to use in estimation": [
                "`'none'`, `'varimax'` (standaard), `'quartimax'`, `'promax'`, `'oblimin'`, of `'simplimax'`, de rotatie gebruikt in de schatting"
            ],
            "`'none'`, `'varimax'`, `'quartimax'`, `'promax'`, `'oblimin'` (default), or `'simplimax'`, the rotation to use in estimation": [
                "`'none'`, `'varimax'`, `'quartimax'`, `'promax'`, `'oblimin'` (standaard), of `'simplimax'`, de rotatie gebruikt in de schatting"
            ],
            "`'notequal'` (default), `'greater'` or `'less'`, the alternative hypothesis": [
                "`'notequal'` (standaard), `'greater'` of `'less'`, de alternatieve hypothese"
            ],
            "`'parallel'` (default), `'eigen'` or `'fixed'`, the way to determine the number of factors": [
                "`'parallel'` (standaard), `'eigen'` of `'fixed'`, de manier waarop het aantal factoren bepaald wordt"
            ],
            "`'perAnalysis'` or `'listwise'`, how to handle missing values; `'perAnalysis'` excludes missing values for individual dependent variables, `'listwise'` excludes a row from all analyses if one of its entries is missing": [
                "`'perAnalysis'` of `'listwise'`, hoe met ontbrekende waarden wordt omgegaan; `'perAnalysis'` sluit ontbrekende waarden uit voor individuele afhankelijke variabelen, `'listwise'` sluit een rij uit van alle analyses als een van de waarden ontbreekt"
            ],
            "`'perAnalysis'` or `'listwise'`, how to handle missing values; `'perAnalysis'` excludes missing values for individual dependent variables, `'listwise'` excludes a row from all analyses if one of its entries is missing.": [
                "`'perAnalysis'` of `'listwise'`, hoe er met ontbrekende waarden omgegaan wordt; `'perAnalysis'` sluit ontbrekende waarden uit voor individuele afhankelijke variabelen, `'listwise'` sluit de hele rij uit van alle analyses als de rij een ontbrekende waarde bevat."
            ],
            "`'refLevel'` (default) or `'grandMean'`, coding of the intercept. Either creates contrast so that the intercept represents the reference level or the grand mean": [
                ""
            ],
            "`'rows'` or `'columns'` (default), display the variables across the rows or across the columns (default)": [
                "`'rows'` orf`'columns'` (standaard), of de variabelen over de rijen of kolommen moeten worden weergegeven"
            ],
            "`'Thurstone'` (default), `'Bartlett'`, `'tenBerge'`, `'Anderson'`, or `'Harman'` use respectively 'Thurstone', 'Bartlett', 'ten Berge', 'Anderson & Rubin', or 'Harman' method for estimating factor scores": [
                ""
            ],
            "`ANCOVA - ${dep}`": [
                "`ANCOVA - ${dep}`"
            ],
            "`ANOVA - ${dep}`": [
                "`ANOVA - ${dep}`"
            ],
            "`columns` or `rows` (default), compare columns/rows in difference of proportions or relative risks (2x2 tables)": [
                ""
            ],
            "`Model Coefficients - ${ dep }`": [
                "`Modelcoëfficiënten - ${ dep }`"
            ],
            "`Model Coefficients - ${dep}`": [
                "`Modelcoëfficiënten - ${dep}`"
            ],
            "`Proportions - ${var}`": [
                "`Proporties - ${var}`"
            ],
            "`TRUE` (default) or `FALSE`, add labels with the row number to the outliers in the box plot": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, perform Student's t-tests": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, perform Welch's one-way ANOVA which does not assume equal variances": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide 'Z' and 'p' values for the model estimates": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide a chi-square test for exact fit that compares the model with the perfect fitting model": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide a confidence interval for the estimated marginal means": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide Aikaike's Information Criterion (AIC) for the models": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide Cronbach's α": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide estimated marginal means plots": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide estimates for the factor (co)variances": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide estimates for the residual (co)variances": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide mean differences for post-hoc tests": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide Pearson's R": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide significance levels": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide significance levels for post-hoc tests": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide the deviance (or -2LogLikelihood) for the models": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide the mean": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide the median": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide the model comparison between the models and the NULL model": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide the number of missing values": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide the sample size": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide the standard deviation": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide the statistical measure `R-squared` for the models": [
                ""
            ],
            "`TRUE` (default) or `FALSE`, provide the statistical measure `R` for the models": [
                "`TRUE` (standaard) of `FALSE`, geef de statistische meting `R` voor de modellen op"
            ],
            "`TRUE` (default) or `FALSE`, provide χ²": [
                "`TRUE` (standaard) of `FALSE`, geef χ² op"
            ],
            "`TRUE` (default) or `FALSE`, weigh each cell equally or weigh them according to the cell frequency": [
                ""
            ],
            "`TRUE` or `FALSE` (default), add counts to the  bar plots": [
                ""
            ],
            "`TRUE` or `FALSE` (default), add mean to box plot": [
                ""
            ],
            "`TRUE` or `FALSE` (default), flag significant correlations": [
                ""
            ],
            "`TRUE` or `FALSE` (default), flag significant post-hoc comparisons": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform a Shapiro-Wilk test on the residuals": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Fisher's one-way ANOVA which assumes equal variances": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform homogeneity tests": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Levene's test for homogeneity of variances": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Levene's tests for homogeneity of variances": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Mann-Whitney U tests": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform pairwise comparisons": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Shapiro-wilk normality tests": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Shapiro-Wilk test of normality": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Shapiro-Wilk tests of normality": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Shapiro-wilk tests of normality": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform sphericity tests": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Welch's t-tests": [
                ""
            ],
            "`TRUE` or `FALSE` (default), perform Wilcoxon signed rank tests": [
                ""
            ],
            "`TRUE` or `FALSE` (default), plot the data on top of the marginal means": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a confidence interval for the model coefficient estimates": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a confidence interval for the model coefficient odds ratio estimates": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a confidence interval for the model coefficient rate ratio estimates": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a confidence interval for the model coefficient standardized estimates": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a confidence interval for the model coefficients": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a confidence interval for the model estimates": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a correlation matrix plot": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a correlation plot": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a cut-off plot": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a descriptive plot": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a path diagram of the model": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a predicted classification table (or confusion matrix)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a Q-Q plot of multivariate normality": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a Q-Q plot of residuals": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a ROC curve plot": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a standardized estimate for the model coefficients": [
                "`TRUE` of `FALSE` (standaard), geef gestandaardiseerde schatting voor de modelcoëfficiënten"
            ],
            "`TRUE` or `FALSE` (default), provide a standardized estimate for the model estimates": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide a z test for differences between two proportions": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Aikaike's Information Criterion (AIC) for the models": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide an exact log odds ratio (requires exact2x2 to be installed)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide bar plots (nominal, ordinal variables only)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Bayes factors": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Bayesian credible intervals": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Bayesian Information Criterion (BIC) for the models": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide box plots (continuous variables only)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Box-Tidwell test for linearity of the logit": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Box's M test": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Cohen's d effect sizes": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide column percentages": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide confidence intervals": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide confidence intervals for the comparative measures": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide confidence intervals for the effect-sizes": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide confidence intervals for the mean": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide confidence intervals for the mean difference": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide confidence intervals for the post-hoc effect sizes": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide densities in the correlation matrix plot": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide density plots (continuous variables only)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide descriptive plots": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide descriptive statistics": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide dot plots (continuous variables only)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide effect sizes": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide effect-sizes": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide estimated marginal means tables": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide estimates for the factor intercepts": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide estimates for the residual intercepts": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Fisher's exact test": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide frequency tables (nominal, ordinal variables only)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide gamma": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide histograms (continuous variables only)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide item means": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide item standard deviations": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide item-rest correlations": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Kendall's tau-b": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Mantel-Haenszel test for trend": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide McDonald's ω": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide means and standard deviations": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide means and standard errors": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide modification indices for the parameters not included in the model": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide N most extreme (highest and lowest) values": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide percentiles": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Phi and Cramer's V": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide posterior plots": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Q-Q plots (continuous variables only)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Q-Q plots of residuals": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide quantiles": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide residual plots where the dependent variable and each covariate is plotted against the standardized residuals.": [
                "`TRUE` of `FALSE` (standaard), geef grafieken van residuen op waarbij de afhankelijke variabele en elke covariaat geplot is tegenover de gestandaardiseerde residuen."
            ],
            "`TRUE` or `FALSE` (default), provide results of the Durbin- Watson test for autocorrelation": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide RMSE for the models": [
                "`TRUE` of `FALSE` (standaard), geef RMSE voor de modellen op"
            ],
            "`TRUE` or `FALSE` (default), provide row percentages": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Shapiro-Wilk p-value": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Shapiro-Wilk test": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide Spearman's rho": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide statistics in the correlation matrix plot": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide summary statistics for the Cook's distance": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide test results (t-value and degrees of freedom) for post-hoc tests": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the contingency coefficient": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the differences in proportions (only available for 2x2 tables)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the expected counts": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the exponential of the log-odds ratio estimate, or the odds ratio estimate": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the exponential of the log-rate ratio estimate, or the rate ratio estimate": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the interquartile range": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the kurtosis": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the likelihood ratio": [
                "`TRUE` of `FALSE` (default), geef de aannemelijkheidsquotiënt op"
            ],
            "`TRUE` or `FALSE` (default), provide the log odds ratio (only available for 2x2 tables)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the maximum": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the mean": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the minimum": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the mode": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the model comparison between the models and the NULL model": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the number of cases": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the observed counts": [
                "`TRUE` of `FALSE` (standaard), geef het aantal waarnemingen op"
            ],
            "`TRUE` or `FALSE` (default), provide the odds ratio (only available for 2x2 tables)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the omnibus ANOVA test for the predictors": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the omnibus likelihood ratio tests for the predictors": [
                "`TRUE` of `FALSE` (default), geef de aannemelijkheidsquotiënttoetsen van omnibus op voor de voorspellers"
            ],
            "`TRUE` or `FALSE` (default), provide the predicted accuracy of outcomes grouped by the cut-off value": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the predicted sensitivity of outcomes grouped by the cut-off value": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the predicted specificity of outcomes grouped by the cut-off value": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the range": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the rea under the ROC curve (AUC)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the relative risk (only available for 2x2 tables)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the residuals for the observed correlation matrix (i.e., the difference between the expected correlation matrix and the observed correlation matrix)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the skewness": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the standard deviation": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the standard error": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the statistical measure `adjusted R-squared` for the models": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the sum": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the thresholds that are used as cut-off scores for the levels of the dependent variable": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide the variance": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide total percentages": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide VIF and tolerence collinearity statistics": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide violin plots (continuous variables only)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide what the Cronbach's α would be if the item was dropped": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide what the McDonald's ω would be if the item was dropped": [
                ""
            ],
            "`TRUE` or `FALSE` (default), provide χ² with continuity correction": [
                ""
            ],
            "`TRUE` or `FALSE` (default), report a summary of the different groups": [
                ""
            ],
            "`TRUE` or `FALSE` (default), set a cut-off used for the predictions": [
                ""
            ],
            "`TRUE` or `FALSE` (default), show barplots": [
                ""
            ],
            "`TRUE` or `FALSE` (default), show Bartlett's test of sphericity results": [
                ""
            ],
            "`TRUE` or `FALSE` (default), show eigenvalue table": [
                ""
            ],
            "`TRUE` or `FALSE` (default), show factor summary": [
                ""
            ],
            "`TRUE` or `FALSE` (default), show inter-factor correlations": [
                ""
            ],
            "`TRUE` or `FALSE` (default), show Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (MSA) results": [
                ""
            ],
            "`TRUE` or `FALSE` (default), show model fit measures and test": [
                ""
            ],
            "`TRUE` or `FALSE` (default), show scree plot": [
                ""
            ],
            "`TRUE` or `FALSE` (default), sort the factor loadings by size": [
                ""
            ],
            "`TRUE` or `FALSE` (default), test for homogeneity of variances (i.e., Levene's test)": [
                ""
            ],
            "`TRUE` or `FALSE` (default), the variables are counts": [
                ""
            ],
            "`TRUE` or `FALSE` (default), whether expected counts should be displayed": [
                ""
            ],
            "`TRUE` or `FALSE` (default); perform an overall model test": [
                ""
            ],
            "±%": [
                "±%"
            ],
            "< Test value": [
                "< toetswaarde"
            ],
            "≠ Test value": [
                "≠ toetswaarde"
            ],
            "> Test value": [
                "> toetswaarde"
            ],
            "⁻ mean - 1SD, <sup>μ</sup> mean, ⁺ mean + 1SD": [
                "⁻ gemiddelde - 1 st.afw., <sup>μ</sup> gemiddelde, ⁺ gemiddelde + 1 st.afw."
            ],
            "1 - Specificity": [
                "1 - specificiteit"
            ],
            "2 Outcomes": [
                "2 uitkomsten"
            ],
            "25,50,75": [
                "25,50,75"
            ],
            "a (semi)partial correlation matrix table": [
                "een (semi)partiële correlatietabel"
            ],
            "a comma-sepated list (default: 25,50,75) specifying the percentiles": [
                ""
            ],
            "a correlation matrix plot": [
                "een correlatiediagram"
            ],
            "a correlation matrix table": [
                "een correlatietabel"
            ],
            "a descriptives plot": [
                "een diagram met beschrijvende statistische waarden"
            ],
            "a formula containing the terms to estimate marginal means for (see the examples)": [
                ""
            ],
            "a formula containing the terms to estimate marginal means for, supports up to three variables per term": [
                ""
            ],
            "a formula containing the terms to perform post-hoc tests on (see the examples)": [
                ""
            ],
            "a formula describing the terms to go into the model (not necessary when providing a formula, see examples)": [
                ""
            ],
            "a list containing named lists that define the `label` of the factor and the `vars` that belong to that factor": [
                ""
            ],
            "a list containing vectors of strings that name the predictors that are added to the model. The elements are added to the model according to their order in the list": [
                ""
            ],
            "a list of character vectors describing the between subjects terms to go into the model": [
                ""
            ],
            "a list of character vectors describing the post-hoc tests that need to be computed": [
                ""
            ],
            "a list of character vectors describing the repeated measures terms to go into the model": [
                ""
            ],
            "a list of lists specifying reference levels of the dependent variable and all the factors": [
                "een lijst van lijsten die de referentieniveaus van de afhankelijke variabele en alle factoren specificeert"
            ],
            "a list of lists specifying the factor and type of contrast to use, one of `'deviation'`, `'simple'`, `'difference'`, `'helmert'`, `'repeated'` or `'polynomial'`": [
                ""
            ],
            "a list of lists specifying the pairs of measurement in `data`": [
                ""
            ],
            "a list of lists specifying the residual covariances that need to be estimated": [
                ""
            ],
            "a list of lists specifying the variables for which the estimated marginal means need to be calculate. Supports up to three variables per term.": [
                ""
            ],
            "a list of lists, where each list decribes a repeated measure (as a string) from `data` defined as `measure` and the particular combination of levels from `rm` that it belongs to (as a vector of strings) defined as `cell`": [
                ""
            ],
            "a list of lists, where each list describes the `label` (as a string) and the `levels` (as vector of strings) of a particular repeated measures factor": [
                ""
            ],
            "A low p-value suggests a violation of the assumption of equal variances": [
                ""
            ],
            "A low p-value suggests a violation of the assumption of normality": [
                ""
            ],
            "A nice correlation data set": [
                "Een mooie correlerende dataset"
            ],
            "a number (default: 0.1), highlight values in the `'corRes'` table above this value": [
                ""
            ],
            "a number (default: 0.3), hide factor loadings below this value": [
                ""
            ],
            "a number (default: 0.3), hide loadings below this value": [
                ""
            ],
            "a number (default: 0.5), the value for the null hypothesis": [
                ""
            ],
            "a number (default: 0), the minimal eigenvalue for a factor to be included in the model": [
                ""
            ],
            "a number (default: 1), the beta prior 'a' parameter": [
                ""
            ],
            "a number (default: 1), the beta prior 'b' parameter": [
                ""
            ],
            "a number (default: 1), the minimal eigenvalue for a component to be included in the model": [
                ""
            ],
            "a number (default: 3), highlight values in the `'modIndices'` tables above this value": [
                ""
            ],
            "a number between 0.01 and 2 (default 0.707), the prior width to use in calculating Bayes factors": [
                ""
            ],
            "a number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors": [
                ""
            ],
            "a number between 0.5 and 2.0 (default 0.707), the prior width to use in calculating Bayes factors": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95) specifying the confidence interval width": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95) specifying the confidence interval width for the estimated marginal means": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95) specifying the confidence interval width that is used as `'ci'`": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95), the confidence interval width": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95), the credible interval width": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95), the width of confidence intervals": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95), the width of confidence intervals for the effect sizes": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95), the width of confidence intervals for the post-hoc effect sizes": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95), the width of confidence intervals to provide": [
                ""
            ],
            "a number between 50 and 99.9 (default: 95), width of the confidence intervals to provide": [
                ""
            ],
            "a number specifying the value of the null hypothesis": [
                ""
            ],
            "a parameter": [
                "a-parameter"
            ],
            "a possible value of `'d'`; provide cohen's d measure of effect size for the post-hoc tests": [
                ""
            ],
            "a post-hoc table": [
                "een post-hoc-tabel"
            ],
            "a proportions table": [
                "een proportietabel"
            ],
            "a q-q plot": [
                "een q-q-plot"
            ],
            "A repeated measures ANOVA data set": [
                ""
            ],
            "a string (default: 'Dependent') describing the label used for the dependent variable throughout the analysis": [
                ""
            ],
            "a string naming a variable in `data` containing counts, or NULL if each row represents a single observation": [
                ""
            ],
            "a string naming the dependent variable from `data`, variable must be a factor": [
                ""
            ],
            "a string naming the dependent variable from `data`, variable must be numeric": [
                ""
            ],
            "a string naming the dependent variable in `data`": [
                ""
            ],
            "a string naming the dependent variables in `data`": [
                ""
            ],
            "a string naming the grouping or independent variable in `data`": [
                ""
            ],
            "a summary of the groups": [
                "een groepsamenvatting"
            ],
            "a table containing estimated marginal means": [
                ""
            ],
            "a table containing factor covariances estimates": [
                ""
            ],
            "a table containing factor intercept estimates": [
                ""
            ],
            "a table containing fit measures": [
                "een tabel met pasvormmetingen"
            ],
            "a table containing modification indices for the factor loadings not included in the model": [
                ""
            ],
            "a table containing modification indices for the residual covariances not included in the model": [
                ""
            ],
            "a table containing residual covariances estimates": [
                ""
            ],
            "a table containing residual intercept estimates": [
                ""
            ],
            "a table containing residuals for the observed correlation matrix": [
                ""
            ],
            "a table containing the chi-square test for exact fit": [
                ""
            ],
            "a table containing the collinearity statistics": [
                ""
            ],
            "a table containing the descriptives": [
                "een tabel met beschrijvende statistiek"
            ],
            "a table containing the factor loadings": [
                ""
            ],
            "a table containing the group descriptives": [
                ""
            ],
            "a table containing the homogeneity of variances tests": [
                ""
            ],
            "a table containing the normality test results": [
                ""
            ],
            "a table containing the normality tests": [
                ""
            ],
            "a table containing the results from the Box-Tidwell test": [
                ""
            ],
            "a table containing the t-test results": [
                ""
            ],
            "a table of ANCOVA results": [
                "een tabel met ANCOVA-resultaten"
            ],
            "a table of ANOVA results": [
                "een tabel met ANOVA-resultaten"
            ],
            "a table of comparative measures": [
                "een tabel met vergelijkende metingen"
            ],
            "a table of homogeneity of variances tests": [
                ""
            ],
            "a table of homogeneity tests": [
                "een tabel met homogeniteitstoetsen"
            ],
            "a table of likelihood ratio tests": [
                "een tabel met aannemelijkheidsquotiënttoetsen"
            ],
            "a table of model coefficient thresholds": [
                ""
            ],
            "a table of model coefficients": [
                "een tabel van modelcoëfficiënten"
            ],
            "a table of normality tests": [
                "een tabel met normaliteitstoetsen"
            ],
            "a table of predicted classifications": [
                "een tabel met voorspelde classificaties"
            ],
            "a table of predictive measures": [
                "een tabel met voorspellende metingen"
            ],
            "a table of proportions": [
                "een proportietabel"
            ],
            "a table of test results": [
                "een tabel met toetsresultaten"
            ],
            "a table of the 'nominal' test results": [
                ""
            ],
            "a table of the descriptive statistics": [
                ""
            ],
            "a table of the Friedman test results": [
                ""
            ],
            "a table of the gamma test results": [
                ""
            ],
            "a table of the Kendall's tau-b test results": [
                ""
            ],
            "a table of the Mantel-Haenszel test for trend": [
                ""
            ],
            "a table of the pairwise comparisons": [
                ""
            ],
            "a table of the proportions": [
                "een tabel met proporties"
            ],
            "a table of the proportions and test results": [
                ""
            ],
            "a table of the test results": [
                ""
            ],
            "a table of χ² test results": [
                "een tabel met χ²-toetsresultaten"
            ],
            "a vector containing strings naming the varibales that are reverse scaled": [
                ""
            ],
            "a vector of numbers: the expected proportions": [
                ""
            ],
            "a vector of strings naming the between subjects factors from `data`": [
                ""
            ],
            "a vector of strings naming the control variables in `data`": [
                ""
            ],
            "a vector of strings naming the covariates from `data`": [
                ""
            ],
            "a vector of strings naming the covariates from `data`. Variables must be numeric": [
                ""
            ],
            "a vector of strings naming the factors from `data`": [
                ""
            ],
            "a vector of strings naming the fixed factors from `data`": [
                ""
            ],
            "a vector of strings naming the repeated measures variables": [
                ""
            ],
            "a vector of strings naming the variables of interest in `data`": [
                ""
            ],
            "a vector of strings naming the variables to correlate in `data`": [
                ""
            ],
            "a vector of strings naming the variables used to split `vars`": [
                ""
            ],
            "Accuracy": [
                "Nauwkeurigheid"
            ],
            "Add New Block": [
                "Nieuw blok toevoegen"
            ],
            "Add New Factor": [
                "Nieuwe factor toevoegen"
            ],
            "Add New Term": [
                "Nieuwe term toevoegen"
            ],
            "Additional Options": [
                "Aanvullende opties"
            ],
            "Additional Output": [
                "Aanvullende uitvoer"
            ],
            "Additional Statistics": [
                "Aanvullende statistieken"
            ],
            "Adjusted R²": [
                "Bijgestelde R²"
            ],
            "AIC": [
                "Akaike-informatiecriterium"
            ],
            "All observations are tied": [
                "Alle waarnemingen zijn verbonden"
            ],
            "Alternative hypothesis": [
                "Alternatieve hypothese"
            ],
            "an array of contrasts tables": [
                "een rij contrasttabellen"
            ],
            "an array of descriptive plots": [
                "een reeks beschrijvende grafieken"
            ],
            "an array of extreme values tables": [
                ""
            ],
            "an array of frequency tables": [
                "een rij frequentietabellen"
            ],
            "an array of groups of plots": [
                ""
            ],
            "an array of model specific results": [
                "een reeks modelspecifieke resultaten"
            ],
            "an array of pairwise comparison tables": [
                ""
            ],
            "an array of post-hoc tables": [
                "een rij post-hoc-tabellen"
            ],
            "an array of Q-Q plots": [
                "een rij Q-Q-plots"
            ],
            "an array of the descriptive plots": [
                ""
            ],
            "an array of the estimated marginal means plots + tables": [
                ""
            ],
            "an array of the posterior plots": [
                ""
            ],
            "an image containing the model path diagram": [
                ""
            ],
            "an image of the descriptive plots": [
                ""
            ],
            "an integer (default: 1), the number of components in the model": [
                ""
            ],
            "an integer (default: 1), the number of factors in the model": [
                ""
            ],
            "an integer (default: 4) specifying the number of equal groups": [
                ""
            ],
            "an integer (default: 5) specifying the number of extreme values": [
                ""
            ],
            "An uninspiring ANOVA data set": [
                "Een ongeïnspireerde ANOVA-dataset"
            ],
            "Analyses bundled with jamovi": [
                "Met jamovi gebundelde analyses"
            ],
            "ANCOVA": [
                "Covariantie-analyse"
            ],
            "Anderson & Rubin": [
                "Anderson & Rubin"
            ],
            "Anderson's Iris Data": [
                "Irisgegevens van Anderson"
            ],
            "ANOVA": [
                "ANOVA"
            ],
            "ANOVA test": [
                "ANOVA-toets"
            ],
            "As there are no between subjects factors specified this assumption is always met.": [
                ""
            ],
            "Assume equal (Fisher's)": [
                "Uitgaan van gelijkheid (Fisher)"
            ],
            "Assumption Checks": [
                "Hypothesetoetsen"
            ],
            "Assumptions": [
                "Hypothesen"
            ],
            "At least one variable must have two levels": [
                ""
            ],
            "AUC": [
                "Oppervlakte onder een kromme"
            ],
            "Autocorrelation": [
                "Autocorrelatie"
            ],
            "Autocorrelation test": [
                "Autocorrelatietoets"
            ],
            "Available for 2x2 tables only": [
                "Alleen beschikbaar voor tabellen van 2x2"
            ],
            "b parameter": [
                "b-parameter"
            ],
            "Bar Plot": [
                "Staafdiagram"
            ],
            "Bar plot": [
                "Staafdiagram"
            ],
            "Bar Plots": [
                "Staafdiagrammen"
            ],
            "Bar Type": [
                "Staaftype"
            ],
            "Bartlett": [
                "Bartlett"
            ],
            "Bartlett's Test of Sphericity": [
                "Sfericiteitstoets van Bartlett"
            ],
            "Bartlett's test of sphericity": [
                "Sfericiteitstoets van Bartlett"
            ],
            "Based on eigenvalue": [
                "Gebaseerd op eigenwaarde"
            ],
            "Based on parallel analysis": [
                "Gebaseerd op parallelle analyse"
            ],
            "Bayes factor": [
                "Bayes-factor"
            ],
            "Bayes factor₁₀": [
                "Bayes-factor₁₀"
            ],
            "Bayesian Statistics": [
                "Bayesiaanse statistieken"
            ],
            "beta 'a' parameter": [
                "bètaparameter 'a'"
            ],
            "beta 'b' parameter": [
                "bètaparameter 'b'"
            ],
            "Between Subject Factors": [
                "Factor tussen elementen"
            ],
            "Between Subjects Components": [
                "Componenten tussen elementen"
            ],
            "Between Subjects Effects": [
                "Effecten tussen elementen"
            ],
            "BIC": [
                "Bayesiaanse informatiecriterium"
            ],
            "Big 5 (Dolan, Oort, Stoel & Wicherts, 2009)": [
                ""
            ],
            "Binomial": [
                "Binomiaal"
            ],
            "Binomial Logistic Regression": [
                "Binomiale logistische regressie"
            ],
            "Binomial Test": [
                "Binomiale toets"
            ],
            "Binomial test": [
                "Binomiale toets"
            ],
            "Block {0}": [
                "Blok {0}"
            ],
            "Block 1": [
                "Blok 1"
            ],
            "Blocks": [
                "Blokken"
            ],
            "Bonferroni": [
                "Bonferroni"
            ],
            "Box plot": [
                "Boxplot"
            ],
            "Box Plots": [
                "Boxplots"
            ],
            "Box-Tidwell test": [
                "Box-Tidwell-toets"
            ],
            "Box-Tidwell Test for Linearity of the Logit": [
                ""
            ],
            "Box's Homogeneity of Covariance Matrices Test": [
                ""
            ],
            "Box's M test": [
                "M-toets van Box"
            ],
            "Box's M test for homogeneity of covariance matrices": [
                ""
            ],
            "Bugs (Ryan, Wilde & Crist, 2013)": [
                ""
            ],
            "Cells": [
                "Cellen"
            ],
            "Central Tendency": [
                "Centrummaten"
            ],
            "CFI": [
                "Vergelijkende aanpassingsindex"
            ],
            "Chi-Square Quantiles": [
                "Chi-kwadraatkwantielen"
            ],
            "CI Lower": [
                "Ondergrens betrouwbaarheidsinterval"
            ],
            "CI Upper": [
                "Bovengrens betrouwbaarheidsinterval"
            ],
            "Classification Table": [
                "Klassificatietabel"
            ],
            "Classification table": [
                "Klassificatietabel"
            ],
            "Classification Table – {dep}": [
                "Classificatietabel – {dep}"
            ],
            "Cohen's d": [
                "d van Cohen"
            ],
            "Collinearity Statistics": [
                "Collineairiteitsstatistieken"
            ],
            "Collinearity statistics": [
                "Collineairiteitsstatistieken"
            ],
            "Column": [
                "Kolom"
            ],
            "Column variable '{var}' contains fewer than 2 levels": [
                ""
            ],
            "Columns": [
                "Kolommen"
            ],
            "columns": [
                "kolommen"
            ],
            "Columns compared": [
                "Kolommen vergeleken"
            ],
            "Comparative Measures": [
                "Vergelijkende metingen"
            ],
            "Comparative Measures (2x2 only)": [
                "Vergelijkende metingen (alleen 2x2)"
            ],
            "Compare": [
                "Vergelijken"
            ],
            "Comparison": [
                "Vergelijking"
            ],
            "Comparisons are based on estimated marginal means": [
                ""
            ],
            "Component": [
                "Component"
            ],
            "Component correlations": [
                "Componentcorrelaties"
            ],
            "Component Loadings": [
                "Componentladingen"
            ],
            "Component scores": [
                "Componentscores"
            ],
            "Component Statistics": [
                "Componentstatistieken"
            ],
            "Component summary": [
                "Componentsamenvatting"
            ],
            "component(s)": [
                "component(en)"
            ],
            "Components": [
                "Componenten"
            ],
            "components": [
                "componenten"
            ],
            "Confidence Interval": [
                "Betrouwbaarheidsinterval"
            ],
            "Confidence interval": [
                "Betrouwbaarheidsinterval"
            ],
            "Confidence interval for Mean": [
                "Betrouwbaarheidsinterval voor gemiddelde"
            ],
            "Confidence interval width": [
                "Breedte betrouwbaarheidsinterval"
            ],
            "Confidence Intervals": [
                "Betrouwbaarheidsintervallen"
            ],
            "Confidence intervals": [
                "Betrouwbaarheidsintervallen"
            ],
            "Confidence level": [
                "Betrouwbaarheidsniveau"
            ],
            "Confirmatory Factor Analysis": [
                "Bevestigende factoranalyse"
            ],
            "Constraints": [
                "Beperkingen"
            ],
            "Contingency coefficient": [
                "Kruiscoëfficiënt"
            ],
            "Contingency Tables": [
                "Kruistabel"
            ],
            "Contrasts": [
                "Contrasten"
            ],
            "Contrasts - $key": [
                "Constrasten - $key"
            ],
            "Control Variables": [
                "Controlevariabelen"
            ],
            "Control variables": [
                "Controlevariabelen"
            ],
            "controlling for {items}": [
                "bepalend voor {items}"
            ],
            "Cook's Distance": [
                "Cook-afstand"
            ],
            "Cook's distance": [
                "Cook-afstand"
            ],
            "Correction": [
                "Correctie"
            ],
            "Corrections": [
                "Correcties"
            ],
            "Correlated": [
                "Gecorreleerd"
            ],
            "Correlated negatively": [
                "Correleert negatief"
            ],
            "Correlated positively": [
                "Correleert positief"
            ],
            "Correlation": [
                "Correlatie"
            ],
            "Correlation Coefficients": [
                "Correlatiecoëfficiënten"
            ],
            "Correlation Heatmap": [
                "Correlatie-heatmap"
            ],
            "Correlation heatmap": [
                "Correlatie-heatmap"
            ],
            "Correlation matrices are a way to examine linear relationships between\ntwo or more continuous variables.": [
                ""
            ],
            "Correlation matrices are a way to examine linear relationships between\ntwo or more continuous variables.\n\nFor each pair of variables, a Pearson's r value indicates the strength\nand direction of the relationship between those two variables. A\npositive value indicates a positive relationship (higher values of one\nvariable predict higher values of the other variable). A negative\nPearson's r indicates a negative relationship (higher values of one\nvariable predict lower values of the other variable, and vice-versa).\nA value of zero indicates no relationship (whether a variable is high\nor low, does not tell us anything about the value of the other\nvariable).\n\nMore formally, it is possible to test the null hypothesis that the\ncorrelation is zero and calculate a p-value. If the p-value is low, it\nsuggests the correlation co-efficient is not zero, and there is a linear\n(or more complex) relationship between the two variables.": [
                ""
            ],
            "Correlation Matrix": [
                "Correlatiematrix"
            ],
            "Correlation matrix": [
                "Correlatiematrix"
            ],
            "Correlation Type": [
                "Correlatietype"
            ],
            "Correlation type": [
                "Correlatietype"
            ],
            "Count": [
                "Tel"
            ],
            "Counts": [
                "Tel"
            ],
            "Counts (optional)": [
                "Tel (optioneel)"
            ],
            "Counts may not be infinite": [
                "Aantallen mogen niet oneindig zijn"
            ],
            "Counts may not be negative": [
                "Aantallen mogen niet negatief zijn"
            ],
            "Counts must be non-negative and finite": [
                ""
            ],
            "Covariates": [
                "Covariaten"
            ],
            "Cox & Snell's R²": [
                "R² van Cox & Snell"
            ],
            "Cramer's V": [
                "Cramers V"
            ],
            "Credible Interval": [
                "Geloofwaardigheidsinterval"
            ],
            "Credible intervals": [
                "Geloofwaardigheidsintervallen"
            ],
            "Cronbach's α": [
                "Cronbachs α"
            ],
            "Cronbach's α (if item is dropped)": [
                ""
            ],
            "cubic": [
                "kubiek"
            ],
            "Cumulative %": [
                "Cumulatief %"
            ],
            "Cut point values": [
                "Snijpuntwaarden"
            ],
            "Cut points for": [
                "Punten verdelen in"
            ],
            "Cut-Off": [
                "Grenswaarde"
            ],
            "Cut-Off Plot": [
                "Grenswaarde grafiek"
            ],
            "Cut-off plot": [
                "Grenswaarde grafiek"
            ],
            "Cut-off value": [
                "Grenswaarde"
            ],
            "dat <- data.frame(\n    `1st survey` = c('Approve', 'Approve', 'Disapprove', 'Disapprove'),\n    `2nd survey` = c('Approve', 'Disapprove', 'Approve', 'Disapprove'),\n    `Counts` = c(794, 150, 86, 570),\n    check.names=FALSE)\n\ncontTablesPaired(formula = Counts ~ `1st survey`:`2nd survey`, data = dat)\n\n#\n#  PAIRED SAMPLES CONTINGENCY TABLES\n#\n#  Contingency Tables\n#  ────────────────────────────────────────────────\n#    1st survey    Approve    Disapprove    Total\n#  ────────────────────────────────────────────────\n#    Approve           794           150      944\n#    Disapprove         86           570      656\n#    Total             880           720     1600\n#  ────────────────────────────────────────────────\n#\n#\n#  McNemar Test\n#  ─────────────────────────────────────────────────────\n#                                Value    df    p\n#  ─────────────────────────────────────────────────────\n#    χ²                           17.4     1    < .001\n#    χ² continuity correction     16.8     1    < .001\n#  ─────────────────────────────────────────────────────\n#\n\n\n# Alternatively, omit the left of the formula (`Counts`) from the\n# formula if each row represents a single observation:\n\ncontTablesPaired(formula = ~ `1st survey`:`2nd survey`, data = dat)": [
                ""
            ],
            "dat <- data.frame(x=c(8, 15))\n\npropTest2(dat, vars = x, areCounts = TRUE)\n\n#\n#  PROPORTION TEST (2 OUTCOMES)\n#\n#  Binomial Test\n#  ───────────────────────────────────────────────────────\n#         Level    Count    Total    Proportion    p\n#  ───────────────────────────────────────────────────────\n#    x    1            8       23         0.348    0.210\n#         2           15       23         0.652    0.210\n#  ───────────────────────────────────────────────────────\n#    Note. Hₐ is proportion ≠ 0.5\n#": [
                ""
            ],
            "Data": [
                "Gegevens"
            ],
            "data <- lavaan::HolzingerSwineford1939\n\njmv::cfa(\n    data = data,\n    factors = list(\n        list(label=\"Visual\", vars=c(\"x1\", \"x2\", \"x3\")),\n        list(label=\"Textual\", vars=c(\"x4\", \"x5\", \"x6\")),\n        list(label=\"Speed\", vars=c(\"x7\", \"x8\", \"x9\"))),\n    resCov = NULL)\n\n#\n#  CONFIRMATORY FACTOR ANALYSIS\n#\n#  Factor Loadings\n#  ─────────────────────────────────────────────────────────────────\n#    Factor     Indicator    Estimate    SE        Z        p\n#  ─────────────────────────────────────────────────────────────────\n#    Visual     x1              0.900    0.0832    10.81    < .001\n#               x2              0.498    0.0808     6.16    < .001\n#               x3              0.656    0.0776     8.46    < .001\n#    Textual    x4              0.990    0.0567    17.46    < .001\n#               x5              1.102    0.0626    17.60    < .001\n#               x6              0.917    0.0538    17.05    < .001\n#    Speed      x7              0.619    0.0743     8.34    < .001\n#               x8              0.731    0.0755     9.68    < .001\n#               x9              0.670    0.0775     8.64    < .001\n#  ─────────────────────────────────────────────────────────────────\n#\n#\n#  FACTOR ESTIMATES\n#\n#  Factor Covariances\n#  ──────────────────────────────────────────────────────────────\n#                          Estimate    SE        Z       p\n#  ──────────────────────────────────────────────────────────────\n#    Visual     Visual      1.000 ᵃ\n#               Textual     0.459      0.0635    7.22    < .001\n#               Speed       0.471      0.0862    5.46    < .001\n#    Textual    Textual     1.000 ᵃ\n#               Speed       0.283      0.0715    3.96    < .001\n#    Speed      Speed       1.000 ᵃ\n#  ──────────────────────────────────────────────────────────────\n#    ᵃ fixed parameter\n#\n#\n#  MODEL FIT\n#\n#  Test for Exact Fit\n#  ────────────────────────\n#    χ²      df    p\n#  ────────────────────────\n#    85.3    24    < .001\n#  ────────────────────────\n#\n#\n#  Fit Measures\n#  ───────────────────────────────────────────────\n#    CFI      TLI      RMSEA     Lower     Upper\n#  ───────────────────────────────────────────────\n#    0.931    0.896    0.0921    0.0714    0.114\n#  ───────────────────────────────────────────────\n#": [
                "data <- lavaan::HolzingerSwineford1939\n\njmv::cfa(\n    data = data,\n    factors = list(\n        list(label=\"Visual\", vars=c(\"x1\", \"x2\", \"x3\")),\n        list(label=\"Textual\", vars=c(\"x4\", \"x5\", \"x6\")),\n        list(label=\"Speed\", vars=c(\"x7\", \"x8\", \"x9\"))),\n    resCov = NULL)\n\n#\n#  BEVESTIGENDE FACTORANALYSE\n#\n#  Factorladingen\n#  ─────────────────────────────────────────────────────────────────\n#    Factor     Indicator    Schatting   St. fout  Z        p\n#  ─────────────────────────────────────────────────────────────────\n#    Visueel    x1              0.900    0.0832    10.81    < .001\n#               x2              0.498    0.0808     6.16    < .001\n#               x3              0.656    0.0776     8.46    < .001\n#    Tekst      x4              0.990    0.0567    17.46    < .001\n#               x5              1.102    0.0626    17.60    < .001\n#               x6              0.917    0.0538    17.05    < .001\n#    Snelheid   x7              0.619    0.0743     8.34    < .001\n#               x8              0.731    0.0755     9.68    < .001\n#               x9              0.670    0.0775     8.64    < .001\n#  ─────────────────────────────────────────────────────────────────\n#\n#\n#  FACTORSCHATTINGEN\n#\n#  Factor-covarianties\n#  ──────────────────────────────────────────────────────────────\n#                          Schatting   St. fout  Z       p\n#  ──────────────────────────────────────────────────────────────\n#    Visueel    Visueel     1.000 ᵃ\n#               Tekst       0.459      0.0635    7.22    < .001\n#               Snelheid    0.471      0.0862    5.46    < .001\n#    Tekst      Tekst       1.000 ᵃ\n#               Snelheid    0.283      0.0715    3.96    < .001\n#    Snelh. Snelheid    1.000 ᵃ\n#  ──────────────────────────────────────────────────────────────\n#    ᵃ vaste parameter\n#\n#\n#  MODELVORM\n#\n#  Toets voor exacte passende vorm\n#  ────────────────────────\n#    χ²      df    p\n#  ────────────────────────\n#    85.3    24    < .001\n#  ────────────────────────\n#\n#\n#  Vormmeting\n#  ───────────────────────────────────────────────\n#    CFI      TLI      RMSEA     Laag      Hoog\n#  ───────────────────────────────────────────────\n#    0.931    0.896    0.0921    0.0714    0.114\n#  ───────────────────────────────────────────────\n#"
            ],
            "Data Reduction": [
                "Gegevensreductie"
            ],
            "Data set is currently unweighted": [
                "Gegevensset is momenteel ongewogen"
            ],
            "Data Summary": [
                "Gegevenssamenvatting"
            ],
            "data('birthwt', package='MASS')\n\ndat <- data.frame(\n            low = factor(birthwt$low),\n            age = birthwt$age,\n            bwt = birthwt$bwt)\n\nlogRegBin(data = dat, dep = low,\n          covs = vars(age, bwt),\n          blocks = list(list(\"age\", \"bwt\")),\n          refLevels = list(list(var=\"low\", ref=\"0\")))\n\n#\n#  BINOMIAL LOGISTIC REGRESSION\n#\n#  Model Fit Measures\n#  ───────────────────────────────────────\n#    Model    Deviance    AIC     R²-McF\n#  ───────────────────────────────────────\n#        1     4.97e-7    6.00     1.000\n#  ───────────────────────────────────────\n#\n#\n#  MODEL SPECIFIC RESULTS\n#\n#  MODEL 1\n#\n#  Model Coefficients\n#  ────────────────────────────────────────────────────────────\n#    Predictor    Estimate      SE          Z           p\n#  ────────────────────────────────────────────────────────────\n#    Intercept    2974.73225    218237.2      0.0136    0.989\n#    age            -0.00653       482.7    -1.35e-5    1.000\n#    bwt            -1.18532        87.0     -0.0136    0.989\n#  ────────────────────────────────────────────────────────────\n#    Note. Estimates represent the log odds of \"low = 1\"\n#    vs. \"low = 0\"\n#\n#": [
                ""
            ],
            "data('birthwt', package='MASS')\n\ndat <- data.frame(\n            race = factor(birthwt$race),\n            age = birthwt$age,\n            low = factor(birthwt$low))\n\nlogRegMulti(data = dat, dep = race,\n            covs = age, factors = low,\n            blocks = list(list(\"age\", \"low\")),\n            refLevels = list(\n                list(var=\"race\", ref=\"1\"),\n                list(var=\"low\", ref=\"0\")))\n\n#\n#  MULTINOMIAL LOGISTIC REGRESSION\n#\n#  Model Fit Measures\n#  ──────────────────────────────────────\n#    Model    Deviance    AIC    R²-McF\n#  ──────────────────────────────────────\n#        1         360    372    0.0333\n#  ──────────────────────────────────────\n#\n#\n#  MODEL SPECIFIC RESULTS\n#\n#  MODEL 1\n#\n#  Model Coefficients\n#  ───────────────────────────────────────────────────────────────\n#    race     Predictor    Estimate    SE        Z         p\n#  ───────────────────────────────────────────────────────────────\n#    2 - 1    Intercept      0.8155    1.1186     0.729    0.466\n#             age           -0.1038    0.0487    -2.131    0.033\n#             low:\n#             1 – 0          0.7527    0.4700     1.601    0.109\n#    3 - 1    Intercept      1.0123    0.7798     1.298    0.194\n#             age           -0.0663    0.0324    -2.047    0.041\n#             low:\n#             1 – 0          0.5677    0.3522     1.612    0.107\n#  ───────────────────────────────────────────────────────────────\n#\n#": [
                ""
            ],
            "data('bugs', package = 'jmv')\n\nanovaRM(\n    data = bugs,\n    rm = list(\n        list(\n            label = 'Frightening',\n            levels = c('Low', 'High'))),\n    rmCells = list(\n        list(\n            measure = 'LDLF',\n            cell = 'Low'),\n        list(\n            measure = 'LDHF',\n            cell = 'High')),\n    rmTerms = list(\n        'Frightening'))\n\n#\n#  REPEATED MEASURES ANOVA\n#\n#  Within Subjects Effects\n#  ───────────────────────────────────────────────────────────────────────\n#                  Sum of Squares    df    Mean Square    F       p\n#  ───────────────────────────────────────────────────────────────────────\n#    Frightening              126     1         126.11    44.2    < .001\n#    Residual                 257    90           2.85\n#  ───────────────────────────────────────────────────────────────────────\n#    Note. Type 3 Sums of Squares\n#\n#\n#\n#  Between Subjects Effects\n#  ─────────────────────────────────────────────────────────────────\n#                Sum of Squares    df    Mean Square    F    p\n#  ─────────────────────────────────────────────────────────────────\n#    Residual               954    90           10.6\n#  ─────────────────────────────────────────────────────────────────\n#    Note. Type 3 Sums of Squares\n#": [
                ""
            ],
            "data('bugs', package = 'jmv')\n\nanovaRMNP(bugs, measures = vars(LDLF, LDHF, HDLF, HDHF))\n\n#\n#  REPEATED MEASURES ANOVA (NON-PARAMETRIC)\n#\n#  Friedman\n#  ────────────────────────\n#    χ²      df    p\n#  ────────────────────────\n#    55.8     3    < .001\n#  ────────────────────────\n#": [
                ""
            ],
            "data('bugs', package = 'jmv')\n\nttestPS(bugs, pairs = list(\n        list(i1 = 'LDLF', i2 = 'LDHF')))\n\n#\n#  PAIRED SAMPLES T-TEST\n#\n#  Paired Samples T-Test\n#  ──────────────────────────────────────────────────────────────\n#                                   statistic    df      p\n#  ──────────────────────────────────────────────────────────────\n#    LDLF    LDHF    Student's t        -6.65    90.0    < .001\n#  ──────────────────────────────────────────────────────────────\n#": [
                ""
            ],
            "data('HairEyeColor')\ndat <- as.data.frame(HairEyeColor)\n\ncontTables(formula = Freq ~ Hair:Eye, dat)\n\n#\n#  CONTINGENCY TABLES\n#\n#  Contingency Tables\n#  ─────────────────────────────────────────────────────\n#    Hair     Brown    Blue    Hazel    Green    Total\n#  ─────────────────────────────────────────────────────\n#    Black       68      20       15        5      108\n#    Brown      119      84       54       29      286\n#    Red         26      17       14       14       71\n#    Blond        7      94       10       16      127\n#    Total      220     215       93       64      592\n#  ─────────────────────────────────────────────────────\n#\n#\n#  χ² Tests\n#  ───────────────────────────────\n#          Value    df    p\n#  ───────────────────────────────\n#    χ²      138     9    < .001\n#    N       592\n#  ───────────────────────────────\n#\n\n# Alternatively, omit the left of the formula (`Freq`) if each row\n# represents a single observation:\n\ncontTables(formula = ~ Hair:Eye, dat)": [
                ""
            ],
            "data('HairEyeColor')\ndat <- as.data.frame(HairEyeColor)\n\npropTestN(formula = Freq ~ Eye, data = dat, ratio = c(1,1,1,1))\n\n#\n#  PROPORTION TEST (N OUTCOMES)\n#\n#  Proportions\n#  ────────────────────────────────\n#    Level    Count    Proportion\n#  ────────────────────────────────\n#    Brown      220         0.372\n#    Blue       215         0.363\n#    Hazel       93         0.157\n#    Green       64         0.108\n#  ────────────────────────────────\n#\n#\n#  χ² Goodness of Fit\n#  ───────────────────────\n#    χ²     df    p\n#  ───────────────────────\n#    133     3    < .001\n#  ───────────────────────\n#": [
                "data('HairEyeColor')\ndat <- as.data.frame(HairEyeColor)\n\npropTestN(formula = Freq ~ Eye, data = dat, ratio = c(1,1,1,1))\n\n#\n#  PROPORTIETOETS (N UITKOMSTEN)\n#\n#  Proporties\n#  ────────────────────────────────\n#    Niveau   Aantal   Proportie\n#  ────────────────────────────────\n#    Bruin      220         0.372\n#    Blauw      215         0.363\n#    Hazel       93         0.157\n#    Groen       64         0.108\n#  ────────────────────────────────\n#\n#\n#  χ²-goodness-of-fit\n#  ───────────────────────\n#    χ²     df    p\n#  ───────────────────────\n#    133     3    < .001\n#  ───────────────────────\n#"
            ],
            "data('iris')\n\nefa(iris, vars = vars(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width))\n\n#\n#  EXPLORATORY FACTOR ANALYSIS\n#\n#  Factor Loadings\n#  ────────────────────────────────────────────────\n#                    1        2        Uniqueness\n#  ────────────────────────────────────────────────\n#    Sepal.Length    0.993                0.10181\n#    Sepal.Width              0.725       0.42199\n#    Petal.Length    0.933                0.00483\n#    Petal.Width     0.897                0.07088\n#  ────────────────────────────────────────────────\n#    Note. 'oblimin' rotation was used\n#": [
                ""
            ],
            "data('iris')\n\nmancova(data = iris,\n    deps = vars(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width),\n    factors = Species)\n\n#\n#  MANCOVA\n#\n#  Multivariate Tests\n#  ───────────────────────────────────────────────────────────────────────────\n#                                     value     F       df1    df2    p\n#  ───────────────────────────────────────────────────────────────────────────\n#    Species    Pillai's Trace          1.19    53.5      8    290    < .001\n#               Wilks' Lambda         0.0234     199      8    288    < .001\n#               Hotelling's Trace       32.5     581      8    286    < .001\n#               Roy's Largest Root      32.2    1167      4    145    < .001\n#  ───────────────────────────────────────────────────────────────────────────\n#\n#\n#  Univariate Tests\n#  ───────────────────────────────────────────────────────────────────────────────────────────────\n#                 Dependent Variable    Sum of Squares    df     Mean Square    F         p\n#  ───────────────────────────────────────────────────────────────────────────────────────────────\n#    Species      Sepal.Length                   63.21      2        31.6061     119.3    < .001\n#                 Sepal.Width                    11.34      2         5.6725      49.2    < .001\n#                 Petal.Length                  437.10      2       218.5514    1180.2    < .001\n#                 Petal.Width                    80.41      2        40.2067     960.0    < .001\n#    Residuals    Sepal.Length                   38.96    147         0.2650\n#                 Sepal.Width                    16.96    147         0.1154\n#                 Petal.Length                   27.22    147         0.1852\n#                 Petal.Width                     6.16    147         0.0419\n#  ───────────────────────────────────────────────────────────────────────────────────────────────\n#": [
                ""
            ],
            "data('iris')\n\npca(iris, vars = vars(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width))\n\n#\n#  PRINCIPAL COMPONENT ANALYSIS\n#\n#  Component Loadings\n#  ────────────────────────────────────────\n#                    1         Uniqueness\n#  ────────────────────────────────────────\n#    Sepal.Length     0.890        0.2076\n#    Sepal.Width     -0.460        0.7883\n#    Petal.Length     0.992        0.0168\n#    Petal.Width      0.965        0.0688\n#  ────────────────────────────────────────\n#    Note. 'varimax' rotation was used\n#": [
                ""
            ],
            "data('iris')\n\nreliability(iris, vars = c('Sepal.Length', 'Sepal.Width', 'Petal.Length', 'Petal.Width'),\n            omegaScale = TRUE)\n\n#\n#  RELIABILITY ANALYSIS\n#\n#  Scale Reliability Statistics\n#  ─────────────────────────────────────────\n#             Cronbach's α    McDonald's ω\n#  ─────────────────────────────────────────\n#    scale           0.708           0.848\n#  ─────────────────────────────────────────\n#": [
                ""
            ],
            "data('mtcars')\n\ncorrMatrix(mtcars, vars = vars(mpg, cyl, disp, hp))\n\n#\n#  CORRELATION MATRIX\n#\n#  Correlation Matrix\n#  ──────────────────────────────────────────────────────────────\n#                           mpg      cyl       disp      hp\n#  ──────────────────────────────────────────────────────────────\n#    mpg     Pearson's r        —    -0.852    -0.848    -0.776\n#            p-value            —    < .001    < .001    < .001\n#\n#    cyl     Pearson's r                  —     0.902     0.832\n#            p-value                      —    < .001    < .001\n#\n#    disp    Pearson's r                            —     0.791\n#            p-value                                —    < .001\n#\n#    hp      Pearson's r                                      —\n#            p-value                                          —\n#  ──────────────────────────────────────────────────────────────\n#": [
                ""
            ],
            "data('mtcars')\n\ncorrPart(mtcars, vars = vars(mpg, cyl, disp), controls = vars(hp))\n\n#\n#  PARTIAL CORRELATION\n#\n#  Partial Correlation\n#  ────────────────────────────────────────────────────\n#                           mpg       cyl       disp\n#  ────────────────────────────────────────────────────\n#    mpg     Pearson's r         —\n#            p-value             —\n#\n#    cyl     Pearson's r    -0.590         —\n#            p-value        < .001         —\n#\n#    disp    Pearson's r    -0.606     0.719        —\n#            p-value        < .001    < .001        —\n#  ────────────────────────────────────────────────────\n#    Note. controlling for 'hp'\n#": [
                "data('mtcars')\n\ncorrPart(mtcars, vars = vars(mpg, cyl, disp), controls = vars(hp))\n\n#\n#  PARTIËLE CORRELATIE\n#\n#  Partiële correlatie\n#  ────────────────────────────────────────────────────\n#                           mpg       cyl       disp\n#  ────────────────────────────────────────────────────\n#    mpg     r van Pearson       —\n#            p-waarde            —\n#\n#    cyl     r van Pearson  -0.590         —\n#            p-waarde       < .001         —\n#\n#    disp    r van Pearson  -0.606     0.719        —\n#            p-waarde       < .001    < .001        —\n#  ────────────────────────────────────────────────────\n#    Let op, is bepalend voor 'hp'\n#"
            ],
            "data('mtcars')\n\ntab <- table('gear'=mtcars$gear, 'cyl'=mtcars$cyl)\ndat <- as.data.frame(tab)\n\nlogLinear(data = dat, factors = vars(gear, cyl),  counts = Freq,\n          blocks = list(list(\"gear\", \"cyl\", c(\"gear\", \"cyl\"))),\n          refLevels = list(\n              list(var=\"gear\", ref=\"3\"),\n              list(var=\"cyl\", ref=\"4\")))\n\n#\n#  LOG-LINEAR REGRESSION\n#\n#  Model Fit Measures\n#  ───────────────────────────────────────\n#    Model    Deviance    AIC     R²-McF\n#  ───────────────────────────────────────\n#        1    4.12e-10    41.4     1.000\n#  ───────────────────────────────────────\n#\n#\n#  MODEL SPECIFIC RESULTS\n#\n#  MODEL 1\n#\n#  Model Coefficients\n#  ──────────────────────────────────────────────────────────────────\n#    Predictor          Estimate     SE          Z            p\n#  ──────────────────────────────────────────────────────────────────\n#    Intercept          -4.71e-16        1.00    -4.71e-16    1.000\n#    gear:\n#    4 – 3                  2.079        1.06        1.961    0.050\n#    5 – 3                  0.693        1.22        0.566    0.571\n#    cyl:\n#    6 – 4                  0.693        1.22        0.566    0.571\n#    8 – 4                  2.485        1.04        2.387    0.017\n#    gear:cyl:\n#    (4 – 3):(6 – 4)       -1.386        1.37       -1.012    0.311\n#    (5 – 3):(6 – 4)       -1.386        1.73       -0.800    0.423\n#    (4 – 3):(8 – 4)      -26.867    42247.17    -6.36e -4    0.999\n#    (5 – 3):(8 – 4)       -2.485        1.44       -1.722    0.085\n#  ──────────────────────────────────────────────────────────────────\n#\n#": [
                "data('mtcars')\n\ntab <- table('gear'=mtcars$gear, 'cyl'=mtcars$cyl)\ndat <- as.data.frame(tab)\n\nlogLinear(data = dat, factors = vars(gear, cyl),  counts = Freq,\n          blocks = list(list(\"gear\", \"cyl\", c(\"gear\", \"cyl\"))),\n          refLevels = list(\n              list(var=\"gear\", ref=\"3\"),\n              list(var=\"cyl\", ref=\"4\")))\n\n#\n#  LOG-LINEAIRE REGRESSIE\n#\n#  Modelvormmetingen\n#  ───────────────────────────────────────\n#    Model    Afwijking   AIC     R²-McF\n#  ───────────────────────────────────────\n#        1    4.12e-10    41.4     1.000\n#  ───────────────────────────────────────\n#\n#\n#  MODEL-SPECIFIEKE RESULTATEN\n#\n#  MODEL 1\n#\n#  Modelcoëfficiënten\n#  ──────────────────────────────────────────────────────────────────\n#    Voorspeller        Schatting    St. fout    Z            p\n#  ──────────────────────────────────────────────────────────────────\n#    Onderschepping    -4.71e-16        1.00    -4.71e-16    1.000\n#    gear:\n#    4 – 3                  2.079        1.06        1.961    0.050\n#    5 – 3                  0.693        1.22        0.566    0.571\n#    cyl:\n#    6 – 4                  0.693        1.22        0.566    0.571\n#    8 – 4                  2.485        1.04        2.387    0.017\n#    gear:cyl:\n#    (4 – 3):(6 – 4)       -1.386        1.37       -1.012    0.311\n#    (5 – 3):(6 – 4)       -1.386        1.73       -0.800    0.423\n#    (4 – 3):(8 – 4)      -26.867    42247.17    -6.36e -4    0.999\n#    (5 – 3):(8 – 4)       -2.485        1.44       -1.722    0.085\n#  ──────────────────────────────────────────────────────────────────\n#\n#"
            ],
            "data('mtcars')\ndat <- mtcars\n\n# frequency tables can be provided for factors\ndat$gear <- as.factor(dat$gear)\n\ndescriptives(dat, vars = vars(mpg, cyl, disp, gear), freq = TRUE)\n\n#\n#  DESCRIPTIVES\n#\n#  Descriptives\n#  ───────────────────────────────────────────\n#               mpg     cyl     disp    gear\n#  ───────────────────────────────────────────\n#    N            32      32      32      32\n#    Missing       0       0       0       0\n#    Mean       20.1    6.19     231    3.69\n#    Median     19.2    6.00     196    4.00\n#    Minimum    10.4    4.00    71.1       3\n#    Maximum    33.9    8.00     472       5\n#  ───────────────────────────────────────────\n#\n#\n#  FREQUENCIES\n#\n#  Frequencies of gear\n#  ────────────────────\n#    Levels    Counts\n#  ────────────────────\n#    3             15\n#    4             12\n#    5              5\n#  ────────────────────\n#\n\n# spliting by a variable\ndescriptives(formula = disp + mpg ~ cyl, dat,\n    median=F, min=F, max=F, n=F, missing=F)\n\n# providing histograms\ndescriptives(formula = mpg ~ cyl, dat, hist=T,\n    median=F, min=F, max=F, n=F, missing=F)\n\n# splitting by multiple variables\ndescriptives(formula = mpg ~ cyl:gear, dat,\n    median=F, min=F, max=F, missing=F)": [
                "data('mtcars')\ndat <- mtcars\n\n# frequentietabellen kunnen als factor worden opgegeven\ndat$gear <- as.factor(dat$gear)\n\ndescriptives(dat, vars = vars(mpg, cyl, disp, gear), freq = TRUE)\n\n#\n#  BESCHRIJVENDE STATISTIEK\n#\n#  Beschrijvende statistiek\n#  ───────────────────────────────────────────\n#               mpg     cyl     disp    gear\n#  ───────────────────────────────────────────\n#    N            32      32      32      32\n#    Ontbrekend    0       0       0       0\n#    Gemiddelde 20.1    6.19     231    3.69\n#    Mediaan    19.2    6.00     196    4.00\n#    Minimum    10.4    4.00    71.1       3\n#    Maximum    33.9    8.00     472       5\n#  ───────────────────────────────────────────\n#\n#\n#  FREQUENTIES\n#\n#  Frequenties van gear\n#  ────────────────────\n#    Niveaus   Tel\n#  ────────────────────\n#    3             15\n#    4             12\n#    5              5\n#  ────────────────────\n#\n\n# op variabele splitsen\ndescriptives(formula = disp + mpg ~ cyl, dat,\n    median=F, min=F, max=F, n=F, missing=F)\n\n# histogrammen opgeven\ndescriptives(formula = mpg ~ cyl, dat, hist=T,\n    median=F, min=F, max=F, n=F, missing=F)\n\n# op meerdere variabelen splitsen\ndescriptives(formula = mpg ~ cyl:gear, dat,\n    median=F, min=F, max=F, missing=F)"
            ],
            "data('Prestige', package='carData')\n\nlinReg(data = Prestige, dep = income,\n       covs = vars(education, prestige, women),\n       blocks = list(list('education', 'prestige', 'women')))\n\n#\n#  LINEAR REGRESSION\n#\n#  Model Fit Measures\n#  ───────────────────────────\n#    Model    R        R²\n#  ───────────────────────────\n#        1    0.802    0.643\n#  ───────────────────────────\n#\n#\n#  MODEL SPECIFIC RESULTS\n#\n#  MODEL 1\n#\n#\n#  Model Coefficients\n#  ────────────────────────────────────────────────────────\n#    Predictor    Estimate    SE         t         p\n#  ────────────────────────────────────────────────────────\n#    Intercept      -253.8    1086.16    -0.234     0.816\n#    women           -50.9       8.56    -5.948    < .001\n#    prestige        141.4      29.91     4.729    < .001\n#    education       177.2     187.63     0.944     0.347\n#  ────────────────────────────────────────────────────────\n#": [
                ""
            ],
            "data('ToothGrowth')\n\nancova(formula = len ~ supp + dose, data = ToothGrowth)\n\n#\n#  ANCOVA\n#\n#  ANCOVA\n#  ───────────────────────────────────────────────────────────────────────\n#                 Sum of Squares    df    Mean Square    F        p\n#  ───────────────────────────────────────────────────────────────────────\n#    supp                    205     1          205.4     11.4     0.001\n#    dose                   2224     1         2224.3    124.0    < .001\n#    Residuals              1023    57           17.9\n#  ───────────────────────────────────────────────────────────────────────\n#\n\nancova(\n    formula = len ~ supp + dose,\n    data = ToothGrowth,\n    postHoc = ~ supp,\n    emMeans = ~ supp)": [
                "data('ToothGrowth')\n\nancova(formula = len ~ supp + dose, data = ToothGrowth)\n\n#\n#  ANCOVA\n#\n#  ANCOVA\n#  ───────────────────────────────────────────────────────────────────────\n#                 Kwadraatsom       df    Gem.-kwadraat  F        p\n#  ───────────────────────────────────────────────────────────────────────\n#    supp                    205     1          205.4     11.4     0.001\n#    dose                   2224     1         2224.3    124.0    < .001\n#    Residuen               1023    57           17.9\n#  ───────────────────────────────────────────────────────────────────────\n#\n\nancova(\n    formula = len ~ supp + dose,\n    data = ToothGrowth,\n    postHoc = ~ supp,\n    emMeans = ~ supp)"
            ],
            "data('ToothGrowth')\n\nANOVA(formula = len ~ dose * supp, data = ToothGrowth)\n\n#\n#  ANOVA\n#\n#  ANOVA\n#  ───────────────────────────────────────────────────────────────────────\n#                 Sum of Squares    df    Mean Square    F        p\n#  ───────────────────────────────────────────────────────────────────────\n#    dose                   2426     2         1213.2    92.00    < .001\n#    supp                    205     1          205.4    15.57    < .001\n#    dose:supp               108     2           54.2     4.11     0.022\n#    Residuals               712    54           13.2\n#  ───────────────────────────────────────────────────────────────────────\n#\n\nANOVA(\n    formula = len ~ dose * supp,\n    data = ToothGrowth,\n    emMeans = ~ supp + dose:supp, # est. marginal means for supp and dose:supp\n    emmPlots = TRUE,              # produce plots of those marginal means\n    emmTables = TRUE)             # produce tables of those marginal means": [
                ""
            ],
            "data('ToothGrowth')\n\nanovaNP(formula = len ~ dose, data=ToothGrowth)\n\n#\n#  ONE-WAY ANOVA (NON-PARAMETRIC)\n#\n#  Kruskal-Wallis\n#  ───────────────────────────────\n#           χ²      df    p\n#  ───────────────────────────────\n#    len    40.7     2    < .001\n#  ───────────────────────────────\n#": [
                ""
            ],
            "data('ToothGrowth')\n\nttestIS(formula = len ~ supp, data = ToothGrowth)\n\n#\n#  INDEPENDENT SAMPLES T-TEST\n#\n#  Independent Samples T-Test\n#  ────────────────────────────────────────────────────\n#                          statistic    df      p\n#  ────────────────────────────────────────────────────\n#    len    Student's t         1.92    58.0    0.060\n#  ────────────────────────────────────────────────────\n#": [
                ""
            ],
            "data('ToothGrowth')\n\nttestOneS(ToothGrowth, vars = vars(len, dose))\n\n#\n#  ONE SAMPLE T-TEST\n#\n#  One Sample T-Test\n#  ──────────────────────────────────────────────────────\n#                           statistic    df      p\n#  ──────────────────────────────────────────────────────\n#    len     Student's t         19.1    59.0    < .001\n#    dose    Student's t         14.4    59.0    < .001\n#  ──────────────────────────────────────────────────────\n#": [
                ""
            ],
            "data('ToothGrowth')\ndat <- ToothGrowth\ndat$dose <- factor(dat$dose)\n\nanovaOneW(formula = len ~ dose, data = dat)\n\n#\n#  ONE-WAY ANOVA\n#\n#  One-Way ANOVA (Welch's)\n#  ────────────────────────────────────────\n#           F       df1    df2     p\n#  ────────────────────────────────────────\n#    len    68.4      2    37.7    < .001\n#  ────────────────────────────────────────\n#": [
                ""
            ],
            "Densities for variables": [
                "Dichtheden voor variabelen"
            ],
            "Density": [
                "Dichtheid"
            ],
            "Dependent": [
                "Afhankelijk"
            ],
            "Dependent Variable": [
                "Afhankelijke variabele"
            ],
            "Dependent variable '{dep}' contains infinite values": [
                "Afhankelijke variabele '{dep}' bevat waarden die oneindig zijn"
            ],
            "Dependent variable '{dep}' contains no data (after removing rows with missing values)": [
                "Afhankelijke variabele '{dep}' bevat geen gegevens (na het verwijderen van rijen met ontbrekende waarden)"
            ],
            "Dependent variable '{dep}' contains only one unique value (after removing rows with missing values)": [
                "Afhankelijke variabele '{dep}' bevat slechts één unieke waarde (na het verwijderen van rijen met ontbrekende waarden)"
            ],
            "Dependent variable '{dep}' must be continuous": [
                "Afhankelijke variabele '{dep}' moet continu zijn"
            ],
            "Dependent Variable Label": [
                "Niveau afhankelijke veriabele"
            ],
            "Dependent Variables": [
                "Afhankelijke variabelen"
            ],
            "Dependent variables are very highly correlated": [
                "Afhankelijke variabelen zijn zeer sterk gecorreleerd"
            ],
            "deprecated": [
                "verouderd"
            ],
            "Descriptive Plot": [
                "Beschrijvende grafiek"
            ],
            "Descriptive plot": [
                "Beschrijvende grafiek"
            ],
            "Descriptives": [
                "Beschrijvende statistiek"
            ],
            "Descriptives are an assortment of summarising statistics, and visualizations which allow exploring the shape and distribution of data. It is good practice to explore your data with descriptives before proceeding to more formal tests.": [
                "Onder beschrijvende statistiek valt een breed scala aan samenvattende statistieken en visualisaties waarmee u de vorm en spreiding van gegevens kunt verkennen. Het is verstandig om uw gegevens te verkennen middels beschrijvende statistieken voordat u doorgaat naar geavanceerdere toetsen."
            ],
            "descriptives plot": [
                "beschrijvende grafiek"
            ],
            "Descriptives Plots": [
                "Beschrijvende grafieken"
            ],
            "Descriptives plots": [
                "Beschrijvende grafieken"
            ],
            "Descriptives Table": [
                "Beschrijvende tabel"
            ],
            "Descriptives table": [
                "Beschrijvende tabel"
            ],
            "Deviance": [
                "Deviantie"
            ],
            "Deviation": [
                "Afwijking"
            ],
            "df": [
                "df"
            ],
            "df1": [
                "df1"
            ],
            "df2": [
                "df2"
            ],
            "Difference": [
                "Verschil"
            ],
            "Difference in 2 proportions": [
                "Verschil in 2 proporties"
            ],
            "Difference in proportions": [
                "Proportieverschillen"
            ],
            "Dispersion": [
                "Dispersie"
            ],
            "Distribution": [
                "Verdeling"
            ],
            "Don't assume equal (Welch's)": [
                "Niet uitgaan van gelijkheid (Welch)"
            ],
            "drag variable here": [
                "sleep variabele hierheen"
            ],
            "drag variables here": [
                "sleep variabelen hierheen"
            ],
            "DSCF pairwise comparisons": [
                "DSCF-paarsgewijze vergelijkingen"
            ],
            "Durbin–Watson Test for Autocorrelation": [
                "Durbin–Watson-toets voor autocorrelatie"
            ],
            "DW Statistic": [
                "Durbin–Watson-statistiek"
            ],
            "Dwass-Steel-Critchlow-Fligner pairwise comparisons": [
                "Paarsgewijze vergelijkingen van Dwass-Steel-Critchlow-Fligner"
            ],
            "Effect Size": [
                "Effectsterkte"
            ],
            "Effect size": [
                "Effectsterkte"
            ],
            "Eigenvalue": [
                "Eigenwaarde"
            ],
            "Eigenvalues": [
                "Eigenwaarden"
            ],
            "Eigenvalues greater than": [
                "Eigenwaarden groter dan"
            ],
            "Empty cells in between subject design: at least one combination of between subject factor levels has 0 observations": [
                ""
            ],
            "Equal cell weights": [
                "Gelijke celgewichten"
            ],
            "equal groups": [
                "gelijke groepen"
            ],
            "error %": [
                "% fout"
            ],
            "Error bars": [
                "Foutstaven"
            ],
            "Estimate": [
                "Schatten"
            ],
            "Estimate (Log Odds Ratio)": [
                "Schatting (log-odds-ratio)"
            ],
            "Estimate (Log Rate Ratio)": [
                "Schatting (log-rate-ratio)"
            ],
            "Estimated Marginal Means": [
                "Geschatte marginale gemiddelden"
            ],
            "Estimated Marginal Means - {term}": [
                "Geschatte marginale gemiddelden - {term}"
            ],
            "Estimates": [
                "Schattingen"
            ],
            "Estimates represent the log odds of …": [
                ""
            ],
            "Estimates represent the log odds of \"{dep} = {level1}\" vs. \"{dep} = {level2}\"": [
                ""
            ],
            "Estimation method": [
                "Schattingsmethode"
            ],
            "Exclude cases analysis by analysis": [
                "Waarden individueel uitsluiten"
            ],
            "Exclude cases listwise": [
                "Waarden lijstmatig uitsluiten"
            ],
            "Excluded": [
                "Uitgesloten"
            ],
            "Expected": [
                "Verwacht"
            ],
            "Expected counts": [
                "Verwacht aantal"
            ],
            "Expected Proportions": [
                "Verwachte proporties"
            ],
            "Exploration": [
                "Verkenning"
            ],
            "Exploratory Factor Analysis": [
                "Verkennende factoranalyse"
            ],
            "Extraction": [
                "Extractie"
            ],
            "Extreme values": [
                "Extreme waarden"
            ],
            "Extreme Values": [
                "Extreme waarden"
            ],
            "Extreme values of $key": [
                "Extreme waarden in $key"
            ],
            "F": [
                "F"
            ],
            "F test": [
                "F-toets"
            ],
            "F-statistic could not be calculated": [
                "F-statistiek kon niet worden berekend"
            ],
            "Factor": [
                "Factor"
            ],
            "Factor '{factor}' has less than two levels. Factors must have at least two levels": [
                ""
            ],
            "Factor '{factor}' needs to have at least 2 levels": [
                ""
            ],
            "Factor '{factorName}' contains no data (after removing rows with missing values)": [
                ""
            ],
            "Factor '{factorName}' contains only a single level (after removing rows with missing values)": [
                ""
            ],
            "Factor '{factorName}' contains unused levels (after removing rows with missing values)": [
                ""
            ],
            "Factor {0}": [
                "Factor {0}"
            ],
            "Factor 1": [
                "Factor 1"
            ],
            "Factor correlations": [
                "Factorcorrelaties"
            ],
            "Factor Covariances": [
                "Factorcovarianties"
            ],
            "Factor covariances": [
                "Factorcovarianties"
            ],
            "Factor Estimates": [
                "Factorschattingen"
            ],
            "Factor Intercepts": [
                "Factoronderscheppingen"
            ],
            "Factor intercepts": [
                "Factoronderscheppingen"
            ],
            "Factor Loadings": [
                "Factorladingen"
            ],
            "Factor Loadings – Modification Indices": [
                "Factorladingen – Modificatie-indices"
            ],
            "Factor scores": [
                "Factorscores"
            ],
            "Factor Statistics": [
                "Factorstatistieken"
            ],
            "Factor summary": [
                "Factorsamenvatting"
            ],
            "Factor variances = 1": [
                "Factorvarianties = 1"
            ],
            "factor(s)": [
                "factor(en)"
            ],
            "Factors": [
                "Factoren"
            ],
            "factors": [
                "factoren"
            ],
            "Fisher's": [
                "Fishers"
            ],
            "Fisher's exact test": [
                "Exacte toets van Fisher"
            ],
            "Fit Measures": [
                "Metingen passend maken"
            ],
            "Fitted": [
                "Gepast"
            ],
            "Fixed Factors": [
                "Vaste factoren"
            ],
            "Fixed number": [
                "Vast aantal"
            ],
            "fixed parameter": [
                "vaste parameter"
            ],
            "Flag significant comparisons": [
                "Significante vergelijkingen markeren"
            ],
            "Flag significant correlations": [
                "Significante overeenkomsten markeren"
            ],
            "flag significant correlations (p < .05) with symbols.": [
                ""
            ],
            "flag significant post-hoc comparisons.": [
                "significante post-hoc-vergelijkingen markeren."
            ],
            "Frequencies": [
                "Frequenties"
            ],
            "Frequencies of $key": [
                "Frequenties van $key"
            ],
            "Frequency tables": [
                "Frequentietabellen"
            ],
            "Friedman": [
                "Friedman"
            ],
            "Full information maximum likelihood": [
                "Maximale aannemelijkheid op basis van volledige informatie"
            ],
            "Games-Howell (unequal variances)": [
                "Games-Howell (ongelijke varianties)"
            ],
            "Games-Howell Post-Hoc Test – {dep}": [
                "Post-hoc-toets van Games-Howell – {dep}"
            ],
            "Gamma": [
                "Gamma"
            ],
            "General Options": [
                "Algemene opties"
            ],
            "Generalised η²": [
                "Gegeneraliseerde η²"
            ],
            "Grand mean (simple coding)": [
                "Algeheel gemiddelde (simpele codering)"
            ],
            "Greenhouse-Geisser": [
                "Greenhouse-Geisser"
            ],
            "Greenhouse-Geisser ε": [
                "Greenhouse-Geisser ε"
            ],
            "Group": [
                "Groep"
            ],
            "Group 1": [
                "Groep 1"
            ],
            "Group 1 < Group 2": [
                "Groep 1 < groep 2"
            ],
            "Group 1 ≠ Group 2": [
                "Groep 1 ≠ groep 2"
            ],
            "Group 1 > Group 2": [
                "Groep 1 > groep 2"
            ],
            "Group 2": [
                "Groep 2"
            ],
            "Group Descriptives": [
                "Beschrijvende statistiek voor groep"
            ],
            "Group Summary": [
                "Groepsamenvatting"
            ],
            "Group summary": [
                "Groepsamenvatting"
            ],
            "Grouping Variable": [
                "Groepeervariabele"
            ],
            "Grouping variable '{a}' has less than 2 levels after missing values are excluded": [
                ""
            ],
            "Grouping variable '{a}' must have exactly 2 levels": [
                ""
            ],
            "Grouping variable '{a}' must not also be a dependent variable": [
                ""
            ],
            "Hₐ is negative correlation": [
                "Hₐ: de correlatie is negatief"
            ],
            "Hₐ is positive correlation": [
                "Hₐ: de correlatie is positief"
            ],
            "Hₐ is proportion {direction} {testValue}": [
                "Hₐ: proportie {direction} {testValue}"
            ],
            "Haldane-Anscombe correction applied": [
                "Correctie van Haldane-Anscombe toegepast"
            ],
            "Harman": [
                "Harman"
            ],
            "Helmert": [
                "Helmert"
            ],
            "hidden": [
                "verborgen"
            ],
            "Hide loadings below": [
                "Ladingen verbergen die lager zijn dan"
            ],
            "Highlight values above": [
                "Waarden markeren die hoger zijn dan"
            ],
            "Histogram": [
                "Histogram"
            ],
            "Histograms": [
                "Histogrammen"
            ],
            "Holm": [
                "Holm"
            ],
            "Homogeneity of Variances Test (Levene's)": [
                "Toets van Levene (homoscedasticiteit)"
            ],
            "Homogeneity test": [
                "Homogeniteitstoets"
            ],
            "Hotelling's Trace": [
                "Wet van Hotelling"
            ],
            "Huynh-Feldt": [
                "Huynh-Feldt"
            ],
            "Huynh-Feldt ε": [
                "Huynh-Feldt ε"
            ],
            "Hypothesis": [
                "Hypothese"
            ],
            "If item dropped": [
                "Als item is laten vallen"
            ],
            "in development": [
                "in ontwikkeling"
            ],
            "include a summary of the groups": [
                ""
            ],
            "Independent Samples": [
                "Onafhankelijke steekproeven"
            ],
            "Independent Samples T-Test": [
                "Onafhankelijke t-toets"
            ],
            "Indicator": [
                "Indicator"
            ],
            "Initial Eigenvalues": [
                "Oorspronkelijke eigenwaarden"
            ],
            "Initial eigenvalues": [
                "Oorspronkelijke eigenwaarden"
            ],
            "Inter-Component Correlations": [
                "Correlaties tussen componenten"
            ],
            "Inter-Factor Correlations": [
                "Correlaties tussen factoren"
            ],
            "Intercept": [
                "Onderscheppen"
            ],
            "Interval": [
                "Interval"
            ],
            "IQR": [
                "Interkwartielafstand"
            ],
            "Item '{item}' consists of one level only": [
                ""
            ],
            "Item '{item}' contains infinite values": [
                "Item '{item}' bevat oneindige waarden"
            ],
            "Item '{item}' contains only missing values": [
                ""
            ],
            "Item '{item}' has no variance": [
                "Item '{item}' heeft geen variantie"
            ],
            "Item '{item}' needs to be numeric": [
                ""
            ],
            "item {item} correlates negatively with the total scale and probably should be reversed": [
                ""
            ],
            "Item Reliability Statistics": [
                "Itembetrouwbaarheidsstatsitiek"
            ],
            "Item Statistics": [
                "Itemstatistieken"
            ],
            "Item-rest correlation": [
                "Item-rest-correlatie"
            ],
            "Items": [
                "Items"
            ],
            "items {items} correlate negatively with the total scale and probably should be reversed": [
                ""
            ],
            "Jittered": [
                "Jitter"
            ],
            "Kendall's Tau B": [
                "Tau B van Kendall"
            ],
            "Kendall's Tau-B": [
                "Kendalls tau-B"
            ],
            "Kendall's Tau-b": [
                "Kendalls tau-b"
            ],
            "Kendall's tau-b": [
                "Kendalls tau-b"
            ],
            "KMO Measure of Sampling Adequacy": [
                "Maat voor steekproefgeschiktheid van Kaiser–Meyer–Olkin"
            ],
            "KMO measure of sampling adequacy": [
                "Maat voor steekproefgeschiktheid van Kaiser–Meyer–Olkin"
            ],
            "Kruskal-Wallis": [
                "Kruskal-Wallis"
            ],
            "Kurtosis": [
                "Kurtosis"
            ],
            "Label outliers": [
                "Uitschieterlabels"
            ],
            "Layers": [
                "Lagen"
            ],
            "Level": [
                "Niveau"
            ],
            "Level 1": [
                "Niveau 1"
            ],
            "Level 2": [
                "Niveau 2"
            ],
            "Levene's test is significant (p < .05), suggesting a violation of the assumption of equal variances": [
                ""
            ],
            "Likelihood": [
                "Waarschijnlijkheid"
            ],
            "Likelihood ratio": [
                "Aannemelijkheidsquotiënt"
            ],
            "Likelihood ratio tests": [
                "Aannemelijkheidsquotiënttoetsen"
            ],
            "linear": [
                "lineair"
            ],
            "Linear Regression": [
                "Lineaire regressie"
            ],
            "Linear regression is used to explore the relationship between a continuous dependent variable, and one or more continuous and/or categorical explanatory variables. Other statistical methods, such as ANOVA and ANCOVA, are in reality just forms of linear regression.": [
                ""
            ],
            "Log odds ratio": [
                "Log odds ratio"
            ],
            "Log odds ratio exact": [
                "Exacte log-odds-ratio"
            ],
            "Log-Linear Regression": [
                "Log-lineaire regressie"
            ],
            "Logistic Regression": [
                "Logistische regressie"
            ],
            "Lower": [
                "Ondergrens"
            ],
            "lower bound": [
                "ondergrens"
            ],
            "MANCOVA": [
                "Multivariate covariantie-analyse"
            ],
            "Mann-Whitney U": [
                "Mann-Whitney U"
            ],
            "Mantel-Haenszel": [
                "Mantel-Haenszel"
            ],
            "Mantel-Haenszel Test for Trend": [
                "Neigingstoets van Mantel-Haenszel"
            ],
            "Marginal Mean": [
                "Marginaal gemiddelde"
            ],
            "Marginal Means": [
                "Marginale gemiddelden"
            ],
            "Marginal means plots": [
                "Grafieken van marginale gemiddelden"
            ],
            "Marginal means tables": [
                "Tabellen van marginale gemiddelden"
            ],
            "Mauchly's W": [
                "Mauchly's W"
            ],
            "Max": [
                "Max"
            ],
            "Maximum": [
                "Maximum"
            ],
            "Maximum likelihood": [
                "Maximale waarschijnlijkheid"
            ],
            "McDonald's ω": [
                "McDonalds ω"
            ],
            "McDonald's ω (if item is dropped)": [
                "McDonalds ω (indien item is laten vallen)"
            ],
            "McFadden's R²": [
                "McFaddens R²"
            ],
            "McNemar requires a 2x2 table": [
                "McNemar vereist een tabel van 2x2"
            ],
            "McNemar Test": [
                "McNemar-toets"
            ],
            "McNemar test": [
                "McNemar-toets"
            ],
            "Mean": [
                "Gemiddelde"
            ],
            "Mean ({ciWidth}% CI)": [
                "Gemiddelde ({ciWidth}%-betrouwbaarheidsinterval)"
            ],
            "Mean Difference": [
                "Gemiddeldeverschil"
            ],
            "Mean difference": [
                "Gemiddeldeverschil"
            ],
            "Mean Dispersion": [
                "Gemiddeldespreiding"
            ],
            "Mean score": [
                "Gemiddeldescore"
            ],
            "Mean Square": [
                "Kwadraat gemiddelde"
            ],
            "Means": [
                "Gemiddelden"
            ],
            "Measure": [
                "Meting"
            ],
            "Measure 1 - Measure 2": [
                "Meting 1 - meting 2"
            ],
            "Measure 1 < Measure 2": [
                "Meting 1 < meting 2"
            ],
            "Measure 1 ≠ Measure 2": [
                "Meting 1 ≠ meting 2"
            ],
            "Measure 1 > Measure 2": [
                "Meting 1 > meting 2"
            ],
            "Measures": [
                "Metingen"
            ],
            "Median": [
                "Mediaan"
            ],
            "Medians": [
                "Medianen"
            ],
            "Method": [
                "Methode"
            ],
            "Min": [
                "Min"
            ],
            "Minimum": [
                "Minimum"
            ],
            "Minimum residual": [
                "Minimumresidu"
            ],
            "Minimum residuals": [
                "Minimumresiduen"
            ],
            "Minimum value": [
                "Minimumwaarde"
            ],
            "Missing": [
                "Ontbrekende waarden"
            ],
            "Missing Values": [
                "Ontbrekende waarden"
            ],
            "Missing values": [
                "Ontbrekende waarden"
            ],
            "Missing values exclusion method": [
                "Uitsluitingsmethode ontbrekende waarden"
            ],
            "Missing Values Method": [
                "Methode ontbrekende waarden"
            ],
            "Mode": [
                "Modus"
            ],
            "Model": [
                "Model"
            ],
            "Model Builder": [
                "Modelbouwer"
            ],
            "Model Coefficients": [
                "Modelcoëfficiënten"
            ],
            "Model Comparisons": [
                "Modelvergelijkingen"
            ],
            "Model Fit": [
                "Modelvorm"
            ],
            "Model Fit Measures": [
                "Modelvormmetingen"
            ],
            "Model fit measures": [
                "Modelvormmetingen"
            ],
            "Model Specific Results": [
                "Modelspecifieke resultaten"
            ],
            "Model Terms": [
                "Modeltermen"
            ],
            "Model Test": [
                "Modeltoets"
            ],
            "Model Thresholds": [
                "Modeldrempelwaarden"
            ],
            "Model thresholds": [
                "Modeldrempelwaarden"
            ],
            "Modification Indices": [
                "Modificatie-indices"
            ],
            "Modification indices": [
                "Modifciatie-indices"
            ],
            "Monte Carlo simulation": [
                "Monte-Carlosimulatie"
            ],
            "More than one mode exists, only the first is reported": [
                "Er bestaat meer dan één modus—alleen de eerste wordt gemeld"
            ],
            "Most extreme": [
                "Buitenste"
            ],
            "MSA": [
                "Meetsysteemanalyse"
            ],
            "Multinomial": [
                "Multinomiaal"
            ],
            "Multinomial Logistic Regression": [
                "Multinomiale logistische regressie"
            ],
            "Multivariate Analysis of (Co)Variance (MANCOVA) is used to explore the relationship between multiple dependent variables, and one or more categorical and/or continuous explanatory variables.": [
                ""
            ],
            "Multivariate Statistics": [
                "Multivariate statistieken"
            ],
            "Multivariate Tests": [
                "Multivariate toetsen"
            ],
            "N": [
                "N"
            ],
            "N Outcomes": [
                "N uitkomsten"
            ],
            "Nagelkerke's R²": [
                "Nagelkerke's R²"
            ],
            "No components have an eigenvalue greater than {value}": [
                ""
            ],
            "No correction": [
                "Geen correctie"
            ],
            "No factors defined. Box's M test is only relevant when model contains factors.": [
                ""
            ],
            "Nominal": [
                "Nominaal"
            ],
            "Non-Parametric": [
                "Niet-parametrisch"
            ],
            "None": [
                "Geen"
            ],
            "none": [
                "geen"
            ],
            "Normal Scaled Items": [
                "Normaal geschaalde items"
            ],
            "Normality": [
                "Normaliteit"
            ],
            "Normality test": [
                "Normaliteitstoets"
            ],
            "Normality Test (Shapiro-Wilk)": [
                "Normaliteitstoets (Shapiro-Wilk)"
            ],
            "Not all coefficients could be estimated (likely due to singular fit)": [
                ""
            ],
            "Not available due to too large number of cases (> 5000).": [
                "Niet beschikbaar omdat het een groot aantal items betreft (> 5000)."
            ],
            "Not enough degrees of freedom to estimate all the model effects": [
                "Vrijheidsgraad te klein om alle modeleffecten in te schatten"
            ],
            "Number of Components": [
                "Aantal componenten"
            ],
            "Number of components": [
                "Aantal componenten"
            ],
            "Number of extreme values": [
                "Aantal extreme waarden"
            ],
            "Number of Factors": [
                "Aantal factoren"
            ],
            "Number of factors": [
                "Aantal factoren"
            ],
            "Number of requested extreme values is higher than the number of rows in the data.": [
                ""
            ],
            "Oblimin": [
                "Oblimin"
            ],
            "oblimin": [
                "oblimin"
            ],
            "Observed": [
                "Waargenomen"
            ],
            "Observed counts": [
                "Waargenomen aantal"
            ],
            "Observed scores": [
                "Waargenomen scores"
            ],
            "octic": [
                "octisch"
            ],
            "Odds Ratio": [
                "Kansverhouding"
            ],
            "Odds ratio": [
                "Kansverhouding"
            ],
            "of total": [
                "van totaal"
            ],
            "Omnibus ANOVA Test": [
                "Omnibus-ANOVA-toets"
            ],
            "Omnibus Likelihood Ratio Tests": [
                "Aannemelijkheidsquotiënttoetsen van Omnibus"
            ],
            "Omnibus Test": [
                "Omnibustoets"
            ],
            "Omnibus Tests": [
                "Omnibustoetsen"
            ],
            "one of `'corr'` (default), `'pos'`, `'neg'` specifying the alernative hypothesis; correlated, correlated positively, correlated negatively respectively.": [
                ""
            ],
            "one of `'part'` (default) or `'semi'` specifying the type of partial correlation to calculate; partial or semipartial correlation.": [
                ""
            ],
            "One or both groups do not contain enough observations": [
                ""
            ],
            "One or both variables are not numeric": [
                ""
            ],
            "One or both variables contain infinite values": [
                ""
            ],
            "One or both variables contain no observations": [
                "Eén of beide variabelen bevatten geen waarnemingen"
            ],
            "One or both variables do not contain enough observations": [
                ""
            ],
            "One or more coefficients in model '{modelNo}' could not be estimated due to perfect collinearity.": [
                ""
            ],
            "one or more of `'cfi'`, `'tli'`, `'srmr'`, `'rmsea'`, `'aic'`, or `'bic'`; use CFI, TLI, SRMR, RMSEA + 90% confidence interval, adjusted AIC, and BIC model fit measures, respectively": [
                ""
            ],
            "one or more of `'eta'`, `'partEta'`, or `'omega'`; use η², partial η², and ω² effect sizes, respectively": [
                ""
            ],
            "one or more of `'none'` (default), `'GG'`, or ``HF``; use no p-value correction, the Greenhouse-Geisser p-value correction, and the Huynh-Feldt p-value correction for shericity, respectively": [
                ""
            ],
            "one or more of `'none'`, `'tukey'` (default), `'scheffe'`, `'bonf'`, or `'holm'`; use no, Tukey, Scheffe, Bonferroni and Holm posthoc corrections, respectively": [
                ""
            ],
            "one or more of `'none'`, `'tukey'`, `'scheffe'`, `'bonf'`, or `'holm'`; provide no, Tukey, Scheffe, Bonferroni, and Holm Post Hoc corrections respectively": [
                ""
            ],
            "one or more of `'pillai'`, `'wilks'`, `'hotel'`, or `'roy'`; use Pillai's Trace, Wilks' Lambda, Hotelling's Trace, and Roy's Largest Root multivariate statistics, respectively": [
                ""
            ],
            "one or more of `'r2mf'`, `'r2cs'`, or `'r2n'`; use McFadden's, Cox & Snell, and Nagelkerke pseudo-R², respectively": [
                ""
            ],
            "One Sample Proportion Tests": [
                "Proportietoetsen voor één steekproef"
            ],
            "One Sample T-Test": [
                "t-toets voor één steekproef"
            ],
            "One-Way ANOVA": [
                "Eenzijdige ANOVA"
            ],
            "One-Way ANOVA (Fisher's)": [
                "Eenzijdige ANOVA (van Fisher)"
            ],
            "One-Way ANOVA (Non-parametric)": [
                "Eenzijdige ANOVA (niet-parametrisch)"
            ],
            "One-Way ANOVA (Welch's)": [
                "Eenzijdige ANOVA (van Welch)"
            ],
            "Options": [
                "Opties"
            ],
            "Ordinal": [
                "Ordinaal"
            ],
            "Ordinal Logistic Regression": [
                "Ordinale logistische regressie"
            ],
            "Ordinal Outcomes": [
                "Ordinale uitkomsten"
            ],
            "Outliers": [
                "Uitschieters"
            ],
            "Output": [
                "Uitvoer"
            ],
            "Overall": [
                "Algeheel"
            ],
            "Overall model": [
                "Algeheel model"
            ],
            "Overall Model Test": [
                "Algehele modeltoets"
            ],
            "Overall model test": [
                "Algehele modeltoets"
            ],
            "p": [
                "p"
            ],
            "p-value": [
                "p-waarde"
            ],
            "p<sub>bonferroni</sub>": [
                "p<sub>bonferroni</sub>"
            ],
            "p<sub>holm</sub>": [
                "p<sub>holm</sub>"
            ],
            "p<sub>scheffe</sub>": [
                "p<sub>scheffe</sub>"
            ],
            "p<sub>tukey</sub>": [
                "p<sub>tukey</sub>"
            ],
            "Paired Samples": [
                "Gepaarde steekproeven"
            ],
            "Paired Samples Contingency Tables": [
                "Kruistabellen voor verbonden steekproeven"
            ],
            "Paired Samples T-Test": [
                "t-toets voor twee steekproeven"
            ],
            "Paired Variables": [
                "Gepaarde variabelen"
            ],
            "Pairwise comparisons - $key": [
                "Paarsgewijze vergelijkingen - $key"
            ],
            "Pairwise Comparisons (Durbin-Conover)": [
                "Paarsgewijze vergelijkingen van Durbin-Conover"
            ],
            "Pairwise comparisons (Durbin-Conover)": [
                "Paarsgewijze vergelijkingen van Durbin-Conover"
            ],
            "Partial": [
                "Deels"
            ],
            "Partial Correlation": [
                "Deelse correlatie"
            ],
            "Partial correlation matrices are a way to examine linear relationships\nbetween two or more continuous variables while controlling for other\nvariables": [
                ""
            ],
            "Partial correlation matrices are a way to examine linear relationships\nbetween two or more continuous variables while controlling for other\nvariables\n\nFor each pair of variables, a Pearson's r value indicates the strength\nand direction of the relationship between those two variables. A\npositive value indicates a positive relationship (higher values of one\nvariable predict higher values of the other variable). A negative\nPearson's r indicates a negative relationship (higher values of one\nvariable predict lower values of the other variable, and vice-versa).\nA value of zero indicates no relationship (whether a variable is high\nor low, does not tell us anything about the value of the other\nvariable).\n\nMore formally, it is possible to test the null hypothesis that the\ncorrelation is zero and calculate a p-value. If the p-value is low, it\nsuggests the correlation co-efficient is not zero, and there is a linear\n(or more complex) relationship between the two variables.": [
                ""
            ],
            "Partial η²": [
                "Deelse η²"
            ],
            "partial η²": [
                "deelse η²"
            ],
            "Path Diagram": [
                "Wegendiagram"
            ],
            "Path diagram": [
                "Wegendiagram"
            ],
            "Pearson": [
                "Pearson"
            ],
            "Pearson correlation cannot be calculated for non-numeric values": [
                ""
            ],
            "Pearson's r": [
                "Pearsons r"
            ],
            "Pearson{}Correlation": [
                "Pearson{}correlatie"
            ],
            "Percentages": [
                "Percentages"
            ],
            "Percentages of total": [
                "Percentages van totaal"
            ],
            "Percentages within {var}": [
                "Percentages binnen {var}"
            ],
            "Percentile": [
                "Percentiel"
            ],
            "Percentile Values": [
                "Percentielwaarden"
            ],
            "Percentile values": [
                "Percentielwaarden"
            ],
            "Percentiles": [
                "Percentielen"
            ],
            "perform a Mann-Whitney U test.": [
                "voer een U-toets van Mann-Whitney uit."
            ],
            "perform a Shapiro-Wilk test of normality. A low p-value suggests the data is not from a normal distribution.": [
                ""
            ],
            "perform an overall model test.": [
                "voer een algehele modeltoets uit."
            ],
            "perform Fisher's (or what might be call 'normal') ANOVAs.": [
                ""
            ],
            "perform Shapiro-Wilk tests of normality. A low p-value suggests the data is not from a normal distribution.": [
                ""
            ],
            "perform Shapiro-Wilk tests of normality. A low p-value suggests the residuals are not normally distributed.": [
                ""
            ],
            "perform Student's independent samples t-tests.": [
                "voer een t-toets van Student voor onafhankelijke steekproeven uit."
            ],
            "perform Student's one-sample t-tests.": [
                "voer t-toetsen van Student uit voor één steekproef."
            ],
            "perform Student's paired samples t-tests.": [
                "voer een t-toets van Student voor gepaarde steekproeven uit."
            ],
            "perform Welch's ANOVAs.": [
                "voer ANOVA's van Welch uit."
            ],
            "perform Welch's tests.": [
                "Welch-toetsen uitvoeren."
            ],
            "perform Wilcoxon signed rank tests.": [
                "voer rangtekentoetsen van Wilcoxon uit."
            ],
            "Phi and Cramer's V": [
                "V van Phi en Cramer"
            ],
            "Phi-coefficient": [
                "Phi-coëfficiënt"
            ],
            "Pillai's Trace": [
                "Pillai's spoor"
            ],
            "Plot": [
                "Grafiek"
            ],
            "plot densities along the diagonal of the correlation matrix plot.": [
                ""
            ],
            "plot the data along with the marginal means.": [
                ""
            ],
            "Plot Type": [
                "Grafiektype"
            ],
            "Plots": [
                "Grafieken"
            ],
            "Polynomial": [
                "Polynomiaal"
            ],
            "Post Hoc Comparisons - {term}": [
                "Post-hoc-vergelijkingen - {term}"
            ],
            "Post Hoc Tests": [
                "Post-Hoc-toetsen"
            ],
            "Post Hoc Tests – $key": [
                "Post-hoc-toetsen – $key"
            ],
            "Post-Hoc Model Performance": [
                "Post-Hoc-modelprestaties"
            ],
            "Post-Hoc Test": [
                "Post-Hoc-toets"
            ],
            "Post-Hoc Tests": [
                "Post-Hoc-toetsen"
            ],
            "Posterior": [
                "Posterior"
            ],
            "Posterior plot": [
                "Posterior-diagram"
            ],
            "Posterior Plots": [
                "Posterior-diagrammen"
            ],
            "Predicted": [
                "Voorspeld"
            ],
            "Predicted probability of … = … (vs … = …)": [
                "Verwachte waarschijnlijkheid van … = … (versus … = …)"
            ],
            "Predicted probability of {dep} = {level1} (vs {dep} = {level2})": [
                "Verwachte waarschijnlijkheid van {dep} = {level1} (versus {dep} = {level2})"
            ],
            "Predicted values": [
                "Voorspelde waarden"
            ],
            "Prediction": [
                "Voorspelling"
            ],
            "Predictive Measures": [
                "Voorspelde metingen"
            ],
            "Predictor": [
                "Voorspeller"
            ],
            "Predictors": [
                "Voorspellers"
            ],
            "Principal axis": [
                "Hoofdas"
            ],
            "Principal axis factoring": [
                "Factorisatie hoofdas"
            ],
            "Principal Component Analysis": [
                "Analyse hoofdcomponent"
            ],
            "Prior": [
                "A priori"
            ],
            "Prior width": [
                "Eerdere breedte"
            ],
            "Probability": [
                "Waarschijnlijkheid"
            ],
            "Promax": [
                "Promax"
            ],
            "promax": [
                "promax"
            ],
            "Proportion": [
                "Proportie"
            ],
            "Proportion Test (2 Outcomes)": [
                "Proportietoets (2 uitkomsten)"
            ],
            "Proportion Test (N Outcomes)": [
                "Proportietoets (N uitkomsten)"
            ],
            "provide a Cohen's d measure of effect size for the post-hoc tests.": [
                ""
            ],
            "provide a confidence interval for the difference between the mean estimate and the test value.": [
                ""
            ],
            "provide a correlation matrix plot.": [
                "geef een correlatiediagram op."
            ],
            "provide a Kendall's tau-b for each combination of variables.": [
                ""
            ],
            "provide a p-value for each correlation co-efficient.": [
                ""
            ],
            "provide a Pearson's r for each combination of variables.": [
                ""
            ],
            "provide a Q-Q plot of residuals -- a plot of the actual residuals against what would be expected if the data were *perfectly* normally distributed. Large deviations from the diagonal line suggest the data is not from a normal distribution.": [
                ""
            ],
            "provide a Spearman's rho for each combination of variables.": [
                ""
            ],
            "provide a table of descriptives for each variable.": [
                ""
            ],
            "provide a table of the estimated marginal means.": [
                ""
            ],
            "provide Bayes factors for the Student's independent samples t-tests.": [
                ""
            ],
            "provide Bayes factors for the Student's one-sample t-tests.": [
                ""
            ],
            "provide Bayes factors for the Student's paired samples t-tests.": [
                ""
            ],
            "provide confidence intervals for Pearson's r.": [
                ""
            ],
            "provide confidence intervals for the effect-sizes": [
                ""
            ],
            "provide confidence intervals for the mean differences.": [
                ""
            ],
            "provide confidence intervals for the post-hoc effect sizes.": [
                ""
            ],
            "provide correlation co-efficients in the correlation matrix plot.": [
                ""
            ],
            "provide descriptive plots for each group.": [
                ""
            ],
            "provide descriptive plots for each variable.": [
                ""
            ],
            "provide descriptives for each group of measurements.": [
                ""
            ],
            "provide descriptives for each group.": [
                "geef beschrijvende statistieken op voor elke groep."
            ],
            "provide descriptives plots.": [
                "geef beschrijvende diagrammen op."
            ],
            "provide effect-sizes (Cohen's D).": [
                "geef effectsterkten op (d van Cohen)."
            ],
            "provide effect-sizes (Cohen's d).": [
                "geef effectsterkten op (d van Cohen)."
            ],
            "provide Levene's test for homogeneity of variances. A low p-value suggests the groups have unequal variances.": [
                ""
            ],
            "provide Levene's tests for the homogeneity of variances. A low p-value suggests the groups have unequal variances.": [
                ""
            ],
            "provide mean differences and standard errors of the mean differences.": [
                ""
            ],
            "provide mean differences with the post-hoc tests.": [
                ""
            ],
            "provide mean differences, and standard errors of the mean differences, between the mean estimate, and the test value.": [
                ""
            ],
            "provide measures of effect size; η², partial η², or ω².": [
                ""
            ],
            "provide p-value corrections for sphericity.": [
                "geef p-waardecorrecties op voor sfericiteit."
            ],
            "provide plots of the estimated marginal means.": [
                ""
            ],
            "provide post-hoc tests.": [
                "geef post-hoc-toetsen op."
            ],
            "provide Q-Q plots of residuals -- a plot of the actual residuals against what would be expected if the data were *perfectly* normally distributed. Large deviations from the diagonal line suggest the data is not from a normal distribution.": [
                ""
            ],
            "provide Q-Q plots of residuals -- a plot of the actual residuals against what would be expected if the data were *perfectly* normally distributed. Large deviations from the diagonal line suggest the residuals are not normally distributed.": [
                ""
            ],
            "provide significance levels for the post-hoc tests.": [
                ""
            ],
            "provide sphericity tests.": [
                "geef sfericiteitstoetsen op."
            ],
            "provide test results (t-value and degrees of freedom) for post-hoc tests.": [
                ""
            ],
            "provide the number of cases.": [
                "geef het aantal waarden op."
            ],
            "Pseudo R²": [
                "Pseudo-R²"
            ],
            "Q-Q": [
                "Q-Q"
            ],
            "Q-Q Plot": [
                "Q-Q-plot"
            ],
            "Q-Q plot": [
                "Q-Q-plot"
            ],
            "Q-Q Plot Assessing Multivariate Normality": [
                "Q-Q-plot die multivariate normaliteit evalueert"
            ],
            "Q-Q plot of multivariate normality": [
                "Q-Q-plot van multivariate normaliteit"
            ],
            "Q-Q plot of residuals": [
                "Q-Q-plot van residuen"
            ],
            "Q-Q Plots": [
                "Q-Q-plots"
            ],
            "Q-Q plots": [
                "Q-Q-plots"
            ],
            "quadratic": [
                "kwadratisch"
            ],
            "quartic": [
                "kwartisch"
            ],
            "Quartimax": [
                "Quartimax"
            ],
            "quartimax": [
                "quartimax"
            ],
            "quintic": [
                "kwintisch"
            ],
            "R": [
                "R"
            ],
            "R²": [
                "R²"
            ],
            "R²<sub>CS</sub>": [
                "R²<sub>CS</sub>"
            ],
            "R²<sub>McF</sub>": [
                "R²<sub>McF</sub>"
            ],
            "R²<sub>N</sub>": [
                "R²<sub>N</sub>"
            ],
            "R²<sub>T</sub>": [
                "R²<sub>T</sub>"
            ],
            "Range": [
                "Bereik"
            ],
            "Rank biserial correlation": [
                "Biseriële rangcorrelatie"
            ],
            "Rate Ratio": [
                "Snelheidsverhouding"
            ],
            "Rate ratio": [
                "Snelheidsverhouding"
            ],
            "Ratio": [
                "Ratio"
            ],
            "Reference Level": [
                "Referentieniveau"
            ],
            "Reference level (dummy coding)": [
                "Referentieniveau (dummycodering)"
            ],
            "Reference Levels": [
                "Referentieniveaus"
            ],
            "Regression": [
                "Regressie"
            ],
            "Relative risk": [
                "Relatief risico"
            ],
            "Reliability Analysis": [
                "Betrouwbaarheidsanalyse"
            ],
            "Repeated": [
                "Herhaald"
            ],
            "Repeated Measures ANOVA": [
                "ANOVA voor herhaalde metingen"
            ],
            "Repeated Measures ANOVA (Non-parametric)": [
                "ANOVA voor herhaalde metingen (niet-parametrisch)"
            ],
            "Repeated Measures Cells": [
                "Cellen met herhaalde metingen"
            ],
            "Repeated Measures Components": [
                "Componenten voor herhaalde metingen"
            ],
            "Repeated Measures Factors": [
                "Factoren voor hehaalde metingen"
            ],
            "Report significance": [
                "Significantie melden"
            ],
            "Represents grand mean": [
                "Representeert het algehele gemiddelde"
            ],
            "Represents reference level": [
                "Representeert het referentieniveau"
            ],
            "Residual": [
                "Residu"
            ],
            "Residual Covariances": [
                "Covarianties van residuen"
            ],
            "Residual covariances": [
                "Covarianties van residuen"
            ],
            "Residual Covariances – Modification Indices": [
                "Covarianties van residu's - modificatie-indices"
            ],
            "Residual Estimates": [
                "Schattingen van residuen"
            ],
            "Residual Intercepts": [
                "Onderscheppingen van residuen"
            ],
            "Residual intercepts": [
                "Onderscheppingen van residuen"
            ],
            "Residual plots": [
                "Grafieken van residuen"
            ],
            "Residual sum of squares and/or degrees of freedom are zero, indicating a perfect fit": [
                ""
            ],
            "Residuals": [
                "Residuen"
            ],
            "Residuals for Observed Correlation Matrix": [
                "Residuen waargenomen correlatiematrix"
            ],
            "Residuals from ANOVA": [
                "Residuen van ANOVA"
            ],
            "Residuals observed correlation matrix": [
                "Residuen waargenomen correlatiematrix"
            ],
            "Residuals Plots": [
                "Grafieken van residuen"
            ],
            "Results": [
                "Resultaten"
            ],
            "reverse scaled item": [
                "omgekeerd geschaald item"
            ],
            "Reverse Scaled Items": [
                "Omgekeerd geschaalde items"
            ],
            "RM Factor {0}": [
                "Factor {0} voor herhaalde metingen"
            ],
            "RM Factor 1": [
                "Factor 1 voor herhaalde metingen"
            ],
            "RMSE": [
                "Wortel-gemiddelde-kwadraatafwijking"
            ],
            "RMSEA": [
                "Schatting wortel-gemiddelde-kwadraatafwijking"
            ],
            "RMSEA 90% CI": [
                "RMSEA-90%-betrouwbaarheidsinterval"
            ],
            "ROC": [
                "ROC"
            ],
            "ROC Curve": [
                "ROC-kromme"
            ],
            "ROC curve": [
                "ROC-kromme"
            ],
            "Rotation": [
                "Rotatie"
            ],
            "Row": [
                "Rij"
            ],
            "Row number": [
                "Rijnummer"
            ],
            "Row variable '{var}' contains fewer than 2 levels": [
                ""
            ],
            "Rows": [
                "Rijen"
            ],
            "rows": [
                "rijen"
            ],
            "rows (default), or columns in bar plot X axis": [
                ""
            ],
            "Rows compared": [
                "Rijen vergeleken"
            ],
            "Roy's Largest Root": [
                "Grootste wortel (Roy)"
            ],
            "Sample Size": [
                "Steekproefomvang"
            ],
            "Save": [
                "Opslaan"
            ],
            "scale": [
                "schaal"
            ],
            "Scale Analysis": [
                "Schaalanalyse"
            ],
            "Scale factor = scale first indicator": [
                ""
            ],
            "Scale Reliability Statistics": [
                "Schaalbetrouwbaarheidsstatistiek"
            ],
            "Scale Statistics": [
                "Schaalstatistiek"
            ],
            "Scheffe": [
                "Scheffe"
            ],
            "Score Component": [
                "Scorecomponent"
            ],
            "Score Factor": [
                "Scorefactor"
            ],
            "Score for component": [
                "Componentscore"
            ],
            "Score for factor {i}. Estimated using the '{fsMethod}' method.": [
                ""
            ],
            "Scree Plot": [
                "Screeplot"
            ],
            "Scree plot": [
                "Screeplot"
            ],
            "SD": [
                "Standaardafwijking"
            ],
            "SE": [
                "Standaardfout"
            ],
            "SE difference": [
                "Verschil in standaardfout"
            ],
            "Semipartial": [
                "Semideels"
            ],
            "Semipartial Correlation": [
                "Semi-partiële correlatie"
            ],
            "Sensitivity": [
                "Sensitiviteit"
            ],
            "septic": [
                "septisch"
            ],
            "set.seed(1337)\n\ny <- factor(sample(1:3, 100, replace = TRUE))\nx1 <- rnorm(100)\nx2 <- rnorm(100)\n\ndf <- data.frame(y=y, x1=x1, x2=x2)\n\nlogRegOrd(data = df, dep = y,\n          covs = vars(x1, x2),\n          blocks = list(list(\"x1\", \"x2\")))\n\n#\n#  ORDINAL LOGISTIC REGRESSION\n#\n#  Model Fit Measures\n#  ───────────────────────────────────────\n#    Model    Deviance    AIC    R²-McF\n#  ───────────────────────────────────────\n#        1         218    226    5.68e-4\n#  ───────────────────────────────────────\n#\n#\n#  MODEL SPECIFIC RESULTS\n#\n#  MODEL 1\n#\n#  Model Coefficients\n#  ────────────────────────────────────────────────────\n#    Predictor    Estimate    SE       Z        p\n#  ────────────────────────────────────────────────────\n#    x1             0.0579    0.193    0.300    0.764\n#    x2             0.0330    0.172    0.192    0.848\n#  ────────────────────────────────────────────────────\n#\n#": [
                ""
            ],
            "sextic": [
                "sextisch"
            ],
            "Shapiro-Wilk": [
                "Shapiro-Wilk"
            ],
            "Shapiro-Wilk Multivariate Normality Test": [
                "Multivariate normaliteitstoets van Shapiro-Wilk"
            ],
            "Shapiro-Wilk p": [
                "p van Shapiro-Wilk"
            ],
            "Shapiro-Wilk test": [
                "Shapiro-Wilk-toets"
            ],
            "Shapiro-Wilk test for multivariate normality": [
                "Toets van Shapiro-Wilk voor multivariate normaliteit"
            ],
            "Shapiro-Wilk W": [
                "W van Shapiro-Wilk"
            ],
            "Side by side": [
                "Naast elkaar"
            ],
            "Simple": [
                "Simpel"
            ],
            "Simplimax": [
                "Simplimax"
            ],
            "simplimax": [
                "simplimax"
            ],
            "Simulations": [
                "Simulaties"
            ],
            "Singular fit encountered; one or more predictor variables are a linear combination of other predictor variables.": [
                ""
            ],
            "Singularity error. Sphericity tests are not available": [
                ""
            ],
            "Skewness": [
                "Scheefheid"
            ],
            "Sort loadings by size": [
                "Ladingen sorteren op grootte"
            ],
            "Spearman": [
                "Spearman"
            ],
            "Spearman's rho": [
                "rho van Spearman"
            ],
            "Specificity": [
                "Specificiteit"
            ],
            "Sphericity Correction": [
                "Sfericiteitscorrectie"
            ],
            "Sphericity corrections": [
                "Sfericiteitscorrecties"
            ],
            "Sphericity tests": [
                "Sfericiteitstoetsen"
            ],
            "Split by": [
                "Gesplitst op"
            ],
            "Squared Mahalanobis Distance": [
                "Kwadratische Mahalanobis-afstand"
            ],
            "SRMR": [
                "SRMR"
            ],
            "SS Loadings": [
                "Som van ladingskwadraten"
            ],
            "stack or side by side (default), barplot type": [
                ""
            ],
            "Stacked": [
                "Gestapeld"
            ],
            "Stand. Estimate": [
                "Standaardschatting"
            ],
            "Standard deviation": [
                "Standaardafwijking"
            ],
            "Standard Error": [
                "Standaardfout"
            ],
            "Standard error": [
                "Standaardfout"
            ],
            "Standardized Estimate": [
                "Gestandaardiseerde schatting"
            ],
            "Standardized estimate": [
                "Gestandaardiseerde schatting"
            ],
            "Standardized Residuals": [
                "Gestandaardiseerde residuen"
            ],
            "Statistic": [
                "Statistiek"
            ],
            "statistic": [
                "statistiek"
            ],
            "Statistics": [
                "Statistieken"
            ],
            "Std. deviation": [
                "Standaardafw."
            ],
            "Std. error kurtosis": [
                "Standaardfout kurtosis"
            ],
            "Std. error mean": [
                "Standaardfout gemiddelde"
            ],
            "Std. error of Mean": [
                "Standaardfout van gemiddelde"
            ],
            "Std. error skewness": [
                "Standaardfout scheefheid"
            ],
            "Student's": [
                "Student"
            ],
            "Student's t": [
                "t van Student"
            ],
            "Student's test": [
                "Student-toets"
            ],
            "Sum": [
                "Som"
            ],
            "Sum of Squares": [
                "Som van kwadraten"
            ],
            "Sum of squares": [
                "Som van kwadraten"
            ],
            "Sum score": [
                "Scoretotaal"
            ],
            "Summary": [
                "Samenvatting"
            ],
            "t": [
                "t"
            ],
            "T-Tests": [
                "t-toetsen"
            ],
            "t-value": [
                "t-waarde"
            ],
            "ten Berge": [
                "Ten Berge"
            ],
            "Term {0}": [
                "Term {0}"
            ],
            "Term 1": [
                "Term 1"
            ],
            "Test for Exact Fit": [
                "Toets voor exact passende vorm"
            ],
            "Test results (t and df)": [
                "Toetsresultaten (t en df)"
            ],
            "Test statistics": [
                "Toetsstatistieken"
            ],
            "Test Value": [
                "Toetswaarde"
            ],
            "Test value": [
                "Toetswaarde"
            ],
            "Tests": [
                "Toetsen"
            ],
            "Tests of Sphericity": [
                "Sfericiteitstoets"
            ],
            "th percentile": [
                "ᵉ percentiel"
            ],
            "The 'iris' data set from R": [
                ""
            ],
            "The 'split by' variable '{var}' contains no data.": [
                ""
            ],
            "the (optional) weights from `data` to be used in the fitting process": [
                "de (optionele) gewichten van `data` die moeten worden gebruikt in het pasproces"
            ],
            "the alternative and null hypotheses;\n\n|              | Alternative (Hₐ)  | Null (H₀)          |\n|--------------|-------------------|--------------------|\n| ≠ Test value | Mean ≠ Test value | Mean = Test value  |\n| > Test value | Mean > Test value | Mean <= Test value |\n| < Test value | Mean < Test value | Mean >= Test value |": [
                "de alternatieve en nulhypothesen;\n\n|               | Alternatief (Hₐ)   | Nul (H₀)            |\n|--------------|-------------------|--------------------|\n| ≠ toetswaarde | gem. ≠ toetswaarde | gem. = toetswaarde  |\n| > toetswaarde | gem. > toetswaarde | gem. <= toetswaarde |\n| < toetswaarde | gem. < toetswaarde | gem. >= toetswaarde |"
            ],
            "the alternative hypothesis.": [
                "de alternatieve hypothese."
            ],
            "the alternative hypothesis. Allows for one-tailed tests.": [
                ""
            ],
            "The Analysis of Covariance (ANCOVA) is used to explore the relationship\nbetween a continuous dependent variable, one or more categorical\nexplanatory variables, and one or more continuous explanatory variables\n(or covariates). It is essentially the same analysis as ANOVA, but\nwith the addition of covariates.": [
                ""
            ],
            "The Analysis of Variance (ANOVA) is used to explore the relationship\nbetween a continuous dependent variable, and one or more categorical\nexplanatory variables.": [
                ""
            ],
            "The Analysis of Variance (ANOVA) is used to explore the relationship\nbetween a continuous dependent variable, and one or more categorical\nexplanatory variables.\n\nANOVA assumes that the residuals are normally distributed, and that the\nvariances of all groups are equal. If one is unwilling to assume that\nthe variances are equal, then a Welch's test can be used instead\n(However, the Welch's test does not support more than one explanatory\nfactor). Alternatively, if one is unwilling to assume that the data is\nnormally distributed, a non-parametric approach (such as Kruskal-Wallis)\ncan be used.": [
                ""
            ],
            "The Analysis of Variance (ANOVA) is used to explore the relationship\nbetween a continuous dependent variable, and one or more categorical\nexplanatory variables. This 'One-Way ANOVA' is a simplified version of\nthe 'normal' ANOVA, allowing only a single explanatory factor, however\nalso providing a Welch's ANOVA. The Welch's ANOVA has the advantage that\nit need not assume that the variances of all groups are equal.": [
                "Variantieanalyse (vaak ANOVA) wordt gebruikt om de verhouding tussen\neen continue afhankelijke variabele en één of meerdere categorische\nvariabelen. Deze 'eenzijdige ANOVA' is een versimpelde versie van de\n'normale' ANOVA die maar één categorische variabele toestaat, maar die\ntoch een ANOVA van Welch biedt. Dat heeft het voordeel dat er niet\naangenomen hoeft te worden dat de varianties van alle groepen gelijk zijn."
            ],
            "The Analysis of Variance (ANOVA) is used to explore the relationship\nbetween a continuous dependent variable, and one or more categorical\nexplanatory variables. This 'One-Way ANOVA' is a simplified version of\nthe 'normal' ANOVA, allowing only a single explanatory factor, however\nalso providing a Welch's ANOVA. The Welch's ANOVA has the advantage that\nit need not assume that the variances of all groups are equal.\n\nFor convenience, this method allows specifying multiple dependent\nvariables, resulting in multiple independent tests.\n\nNote that the Welch's ANOVA is the same procedure as the Welch's\nindependent samples t-test.": [
                ""
            ],
            "the between subjects factors (optional).": [
                "de factoren binnen elementen (optioneel)."
            ],
            "the between subjects terms of the model.": [
                "de modeltermen die van toepassing zijn tussen elementen."
            ],
            "The Binomial test is used to test the Null hypothesis that the proportion of observations match some expected value. If the p-value is low, this suggests that the Null hypothesis is false, and that the true proportion must be some other value.": [
                "De binomiale toets wordt gebruikt om de nulhypothese, dat de steekproefproportie overeenkomt met een verwachte waarde, te toetsen. Een lage p-waarde duidt erop dat de nulhypothese onjuist is. De ware proportie moet dan gelijk zijn aan een andere waarde."
            ],
            "the categorical explanatory (or independent) variables.": [
                "de categorische verklarende (of onafhankelijke) variabelen."
            ],
            "The CI of the mean assumes sample means follow a t-distribution with N - 1 degrees of freedom": [
                ""
            ],
            "the confidence interval width for the effect-sizes.": [
                ""
            ],
            "the confidence interval width for the post-hoc effect sizes.": [
                ""
            ],
            "the confidence interval width.": [
                "de breedte van het betrouwbaarheidsinterval."
            ],
            "the continuous explanatory (or independent) variables, also known as covariates.": [
                ""
            ],
            "the contrasts to use.": [
                "de contrasten die moeten worden gebruikt."
            ],
            "the control variables of interest.": [
                "de betreffende controlevariabelen."
            ],
            "the counts in `data`": [
                "de aantallen in `data`"
            ],
            "the covariates (specifying these makes this an ANCOVA)": [
                ""
            ],
            "the covariates from `data`": [
                "de covariaten van `data`"
            ],
            "The cut-off value is set to {}": [
                "De afsnijdwaarde is {}"
            ],
            "the data as a data frame": [
                "gegevens als dataframe"
            ],
            "The dataset contains 0 rows (after removing rows with missing values)": [
                "De dataset bevat 0 rijen (na verwijderen van rijen met ontbrekende waarden)"
            ],
            "The dataset contains 0 rows (or all rows contain missing values)": [
                "De dataset bevat 0 rijen (of alle rijen bevatten ontbrekende waarden)"
            ],
            "The dependent variable '{}' has more than two levels; binomial logistic regression can only be performed on dependent variables with two levels.": [
                "De afhankelijke variabele '{}' heeft meer dan twee niveaus. Binomiale logistische regressie kan alleen worden toegepast op afhankelijke variabelen die binomiaal zijn (twee niveaus hebben)."
            ],
            "The dependent variable '{dep}' has the following order: {orderedLevels}": [
                "De afhankelijke variabele '{dep}' heeft als volgorde: {orderedLevels}"
            ],
            "The dependent variable \"{dep}\" has only two levels, consider doing a binomial logistic regression.": [
                "De afhankelijke variabele '{dep}' heeft slechts twee niveaus. Overweeg een binomiale logistische regressie toe te passen."
            ],
            "the dependent variable from `data`, variable must be numeric": [
                "de afhankelijke variabele uit `data`, moet numeriek zijn"
            ],
            "the dependent variable from `data`, variable must be numeric (not necessary when providing a formula, see examples)": [
                "de afhankelijke variabele uit `data`, moet numeriek zijn (niet vereist wanneer een formule wordt opgegeven, zie voorbeelden)"
            ],
            "the dependent variable. For ANCOVA, these will be continuous.": [
                "de afhankelijke variabele. Voor ANCOVA moet deze continu zijn."
            ],
            "the dependent variable. For ANOVA, these will be continuous.": [
                "de afhankelijke variabele. Voor ANOVA moet deze continu zijn."
            ],
            "the dependent variables -- a separate t-test is performed for each dependent variable specified.": [
                "de afhankelijke variabelen -- een losse t-toets wordt uitgevoerd voor elke opgegeven afhankelijke variabele."
            ],
            "the dependent variables (not necessary when using a formula, see the examples)": [
                "de afhankelijke variabele (niet vereist bij het gebruiken van een formule, zie voorbeelden)"
            ],
            "the dependent variables. For ANOVA, these will be continuous.": [
                "de afhankelijke variabelen. Voor ANOVA moeten deze continu zijn."
            ],
            "the error bars to plot on the marginal means.": [
                "de foutbalken die op de marginale gemiddelden geplot moeten worden."
            ],
            "the explanatory covariates (not necessary when providing a formula, see examples)": [
                ""
            ],
            "the explanatory factors in `data` (not necessary when providing a formula, see examples)": [
                ""
            ],
            "the explanatory or independent variable. For ANOVA this will be categorical.": [
                ""
            ],
            "the explanatory or independent variables. For ANOVA these will be categorical.": [
                ""
            ],
            "the fixed factors from `data`": [
                "de vaste factoren van `data`"
            ],
            "The Friedman test is used to explore the relationship between a continuous dependent variable and a categorical explanatory variable, where the explanatory variable is 'within subjects' (where multiple measurements are from the same subject). It is analagous to Repeated Measures ANOVA, but with the advantage of being non-parametric, and not requiring the assumptions of normality or homogeneity of variances. However, it has the limitation that it can only test a single explanatory variable at a time.": [
                ""
            ],
            "the grouping variable with two levels (not necessary when using a formula, see the examples)": [
                ""
            ],
            "The Kruskal-Wallis test is used to explore the relationship between a continuous dependent variable, and a categorical explanatory variable. It is analagous to ANOVA, but with the advantage of being non-parametric and having fewer assumptions. However, it has the limitation that it can only test a single explanatory variable at a time.": [
                ""
            ],
            "the label to use for the dependent variable.": [
                ""
            ],
            "the lavaan syntax used to fit the model": [
                ""
            ],
            "the missing value exclusion method. `Analysis by analysis` excludes missing values from each analysis. `Listwise` excludes a row from all analyses if one of its values is missing.": [
                ""
            ],
            "the missing value exclusion method. `Analysis by analysis` excludes missing values from each variable. `Listwise` excludes a row from all analyses if one of its values is missing.": [
                ""
            ],
            "the model terms which make up the model.": [
                ""
            ],
            "the model terms which make up the model. By default a full factorial model is created, but here the exact terms making up the model can be adjusted.": [
                ""
            ],
            "the pairs of measurements -- a separate t-test is performed for each pair of measurements.": [
                ""
            ],
            "the post-hoc multiple comparisons corrections to use.": [
                ""
            ],
            "the prior width for the Student's t-test's Bayes factors. Requires a value between 0.01 and 2.0, default 0.707.": [
                ""
            ],
            "the prior width for the Student's t-test's Bayes factors. Requires a value between 0.5 and 2.0, default 0.707.": [
                ""
            ],
            "The Repeated Measures ANOVA is used to explore the relationship\nbetween a continuous dependent variable and one or more categorical\nexplanatory variables, where one or more of the explanatory variables\nare 'within subjects' (where multiple measurements are from the same\nsubject). Additionally, this analysis allows the inclusion of\ncovariates, allowing for repeated measures ANCOVAs as well.": [
                "De 'ANOVA voor herhaalde metingen' wordt gebruikt om de verhouding\ntussen een continue afhankelijke variabele en één of meerdere categorische\nvariabelen te verkennen, waarbij minstens één van de categorische variabelen\n'binnen onderwerpen' zijn (meerdere metingen van hetzelfde onderwerp).\nBij deze analyse kunnen covariaten worden ingesloten, wat 'ANOVA voor\nherhaalde metingen' toestaat."
            ],
            "The Repeated Measures ANOVA is used to explore the relationship\nbetween a continuous dependent variable and one or more categorical\nexplanatory variables, where one or more of the explanatory variables\nare 'within subjects' (where multiple measurements are from the same\nsubject). Additionally, this analysis allows the inclusion of\ncovariates, allowing for repeated measures ANCOVAs as well.\n\nThis analysis requires that the data be in 'wide format', where each\nrow represents a subject (as opposed to long format, where each\nmeasurement of the dependent variable is represented as a row).\n\nA non-parametric equivalent of the repeated measures ANOVA also exists;\nthe Friedman test. However, it has the limitation of only being able to\ntest a single factor.": [
                ""
            ],
            "the repeated measures design.": [
                "het design voor herhaalde metingen."
            ],
            "The repeated measures has only two levels. The assumption of sphericity is always met when the repeated measures has only two levels": [
                ""
            ],
            "The repeated measures has only two levels. The assumption of sphericity is always met when the repeated measures has only two levels.": [
                ""
            ],
            "the repeated measures measurements.": [
                "de metingen voor herhaalde metingen."
            ],
            "the repeated measures terms of the model.": [
                ""
            ],
            "The Student's Independent samples t-test (sometimes called a two-samples\nt-test) is used to test the null hypothesis that two groups have the\nsame mean. A low p-value suggests that the null hypothesis is not true,\nand therefore the group means are different.": [
                ""
            ],
            "The Student's Independent samples t-test (sometimes called a two-samples\nt-test) is used to test the null hypothesis that two groups have the\nsame mean. A low p-value suggests that the null hypothesis is not true,\nand therefore the group means are different.\n\nThe Student's independent t-test assumes that the data from each group\nare from a normal distribution, and that the variances of these groups\nare equal. If unwilling to assume the groups have equal variances, the\nWelch's t-test can be used in it's place. If one is additionally\nunwilling to assume the data from each group are from a normal\ndistribution, the non-parametric Mann-Whitney U test can be used instead\n(However, note that the Mann-Whitney U test has a slightly different\nnull hypothesis; that the distributions of each group is equal).": [
                ""
            ],
            "The Student's One-sample t-test is used to test the null hypothesis that\nthe true mean is equal to a particular value (typically zero). A low\np-value suggests that the null hypothesis is not true, and therefore\nthe true mean must be different from the test value.": [
                ""
            ],
            "The Student's One-sample t-test is used to test the null hypothesis that\nthe true mean is equal to a particular value (typically zero). A low\np-value suggests that the null hypothesis is not true, and therefore\nthe true mean must be different from the test value.\n\nThe Student's One-sample t-test assumes that the data are from a normal\ndistribution -- in the case that one is unwilling to assume this, the\nnon-parametric Wilcoxon signed-rank can be used in it's place (However,\nnote that the Wilcoxon signed-rank has a slightly different null\nhypothesis; that the *median* is equal to the test value).": [
                ""
            ],
            "The Student's paired samples t-test (sometimes called a\ndependent-samples t-test) is used to test the null hypothesis that the\ndifference between pairs of measurements is equal to zero. A low p-value\nsuggests that the null hypothesis is not true, and that the\ndifference between the measurement pairs is not zero.": [
                ""
            ],
            "The Student's paired samples t-test (sometimes called a\ndependent-samples t-test) is used to test the null hypothesis that the\ndifference between pairs of measurements is equal to zero. A low p-value\nsuggests that the null hypothesis is not true, and that the\ndifference between the measurement pairs is not zero.\n\nThe Student's paired samples t-test assumes that pair differences follow\na normal distribution -- in the case that one is unwilling to assume\nthis, the non-parametric Wilcoxon signed-rank can be used in it's place\n(However, note that the Wilcoxon signed-rank has a slightly different\nnull hypothesis; that the two groups of measurements follow the same\ndistribution).": [
                ""
            ],
            "the terms to provide estimated marginal means for. Here you can specify multiple terms.": [
                ""
            ],
            "the test value to test against (typically zero).": [
                ""
            ],
            "the type of correlation to calculate": [
                ""
            ],
            "the type of sums of squares to use; Type 1, 2, or 3.": [
                ""
            ],
            "the type of sums of squares to use; Type 2, or 3.": [
                ""
            ],
            "The underlying `aov` object": [
                "Het onderliggende `aov`-object"
            ],
            "The variable {var} cannot be treated as numeric. Plots that expect numeric data will not be created for this variable.": [
                ""
            ],
            "the variable of interest in `data` (not necessary when using a formula, see the examples)": [
                ""
            ],
            "the variable specifying the groups; must have 2 levels.": [
                ""
            ],
            "the variable to use as the columns in the contingency table (not necessary when providing a formula, see the examples)": [
                ""
            ],
            "the variable to use as the counts in the contingency table (not necessary when providing a formula, see the examples)": [
                ""
            ],
            "the variable to use as the rows in the contingency table (not necessary when providing a formula, see the examples)": [
                ""
            ],
            "The variables {vars} cannot be treated as numeric. Plots that expect numeric data will not be created for these variables.": [
                ""
            ],
            "the variables of interest -- a separate t-test is performed for each variable specified.": [
                ""
            ],
            "the variables of interest.": [
                "de relevante variabelen."
            ],
            "the variables to use to split the contingency table (not necessary when providing a formula, see the examples)": [
                ""
            ],
            "the width for the Confidence intervals.": [
                ""
            ],
            "The χ² Goodness of fit test (not to be confused with the χ² test of independence), tests the Null hypothesis that the proportions of observations match some expected proportions. If the p-value is low, this suggests that the Null hypothesis is false, and that the true proportions are different to those tested.": [
                "De χ²-goodness-of-fittoets (niet te verwarren met de χ²-onafhankelijkheidstoets) toetst de nulhypothese dat de steekproefproporties overeenkomen met de verwachte proporties. Een lage p-waarde suggereert dat deze nulhypothese onjuist is en dat de ware proporties dus afwijken van de getoetste proporties."
            ],
            "The χ² test of association (not to be confused with the χ² goodness of fit) is used to test whether two categorical variables are independent or associated. If the p-value is low, it suggests the variables are not independent, and that there is a relationship between the two variables.": [
                "De χ²-toets voor afhankelijkheid (niet te verwarren met de χ²-goodness-of-fit) wordt gebruikt om na te gaan of twee categorische variabelen afhankelijk dan wel onafhankelijk zijn. Een lage p-waarde suggereert dat er een verband is tussen de variabelen en dat ze dus niet onafhankelijk zijn."
            ],
            "Theoretical Quantiles": [
                "Theoretische kwantielen"
            ],
            "This module represents the analyses included with jamovi. It contains many common analyses (such as t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, factor analysis, etc).": [
                ""
            ],
            "Threshold": [
                "Drempelwaarde"
            ],
            "Thresholds": [
                "Drempelwaarden"
            ],
            "Thurstone": [
                "Thurstone"
            ],
            "Tjur's R²": [
                "R² van Tjur"
            ],
            "TLI": [
                "TLI"
            ],
            "Tolerance": [
                "Tolerantie"
            ],
            "Too few observations (N < 3) to compute statistic": [
                ""
            ],
            "Too few observations to calculate statistic. Each (sub)group must have at least as many observations as there are dependent variables.": [
                ""
            ],
            "Too few samples to compute statistic (N < {n})": [
                ""
            ],
            "Too few samples to compute statistic (N < 3)": [
                ""
            ],
            "Too many observations (N > 5000) to compute statistic": [
                ""
            ],
            "Too many samples to compute statistic (N > {n})": [
                ""
            ],
            "Too many samples to compute statistic (N > 5000)": [
                ""
            ],
            "Tooth Growth": [
                "Tandgroei"
            ],
            "Total": [
                "Totaal"
            ],
            "total_pc (default), column_pc, or row_pc. Use respectively percentages `of total`, `within columns`, or `within rows` for the bar plot y-axis.": [
                ""
            ],
            "Tukey": [
                "Tukey"
            ],
            "Tukey (equal variances)": [
                "Tukey (gelijke varianties)"
            ],
            "Tukey Post-Hoc Test – {dep}": [
                "Post-Hoctoets van Tukey – {dep}"
            ],
            "Type {ssType} Sums of Squares": [
                "Kwadraatsommen type {ssType}"
            ],
            "Type 1": [
                "Type 1"
            ],
            "Type 2": [
                "Type 2"
            ],
            "Type 3": [
                "Type 3"
            ],
            "Type 3 sum of squares": [
                "Kwadraatsommen type 3"
            ],
            "Unable to split by a continuous variable": [
                ""
            ],
            "Uniqueness": [
                "Uniekheid"
            ],
            "Univariate Tests": [
                "Univariate toetsen"
            ],
            "Upper": [
                "Bovengrens"
            ],
            "upper bound": [
                "bovengrens"
            ],
            "Value": [
                "Waarde"
            ],
            "value": [
                "waarde"
            ],
            "values": [
                "waarden"
            ],
            "Values are counts": [
                "Waarden zijn de tel"
            ],
            "Variable": [
                "Variabele"
            ],
            "Variable '{var}' contains no data": [
                "Variabele '{var}' bevat geen waarden"
            ],
            "Variable contains infinite values": [
                "Variabele bevat oneindige waarden"
            ],
            "Variable does not contain enough observations": [
                "Variabele heeft niet genoeg waarnemingen"
            ],
            "Variable is not numeric": [
                "Variabele is niet numeriek"
            ],
            "Variables": [
                "Variabelen"
            ],
            "Variables across columns": [
                "Variabelen over kolommen"
            ],
            "Variables across rows": [
                "Variabelen over rijen"
            ],
            "Variables must have at least two levels": [
                ""
            ],
            "Variance": [
                "Variantie"
            ],
            "Variances": [
                "Varianties"
            ],
            "variation from the control variables is only removed from the variables in the columns": [
                ""
            ],
            "Varimax": [
                "Varimax"
            ],
            "varimax": [
                "varimax"
            ],
            "VIF": [
                "VIF"
            ],
            "Violin": [
                "Violin"
            ],
            "W": [
                "W"
            ],
            "weigh each cell equally. (Cells are weighed according to the cell frequency by default.)": [
                ""
            ],
            "Weight Variable": [
                "Weegvariabele"
            ],
            "Weighted by '{varName}'": [
                "Gewicht bepaald door '{varName}'"
            ],
            "Weights": [
                "Weegfactoren"
            ],
            "Weights (optional)": [
                "Gewichten (optioneel)"
            ],
            "Weights contains negative values. Negative weights are not permitted.": [
                ""
            ],
            "Welch's": [
                "Welch's"
            ],
            "Welch's t": [
                "t van Welch"
            ],
            "Wilcoxon rank": [
                "Wilcoxon-rang"
            ],
            "Wilcoxon signed rank test": [
                "Rangtekentoets van Wilcoxon"
            ],
            "Wilcoxon W": [
                "W van Wilcoxon"
            ],
            "Wilks' Lambda": [
                "Labda van Wilks"
            ],
            "within column": [
                "binnen kolom"
            ],
            "within rows": [
                "binnen rijen"
            ],
            "Within Subjects Effects": [
                "Effecten binnen elementen"
            ],
            "X-Axis": [
                "X-as"
            ],
            "X-axis": [
                "X-as"
            ],
            "Y-Axis": [
                "Y-as"
            ],
            "Y-axis": [
                "Y-as"
            ],
            "ycounts (default) or ypc. Use respectively `counts` or `percentages` for the bar plot y-axis": [
                ""
            ],
            "Z": [
                "Z"
            ],
            "z test difference in 2 proportions": [
                ""
            ],
            "z test for difference in 2 proportions": [
                ""
            ],
            "z test only available for 2x2 tables": [
                ""
            ],
            "ΔR²": [
                "ΔR²"
            ],
            "ε²": [
                "ε²"
            ],
            "η²": [
                "η²"
            ],
            "η²<sub>G</sub>": [
                "η²<sub>G</sub>"
            ],
            "η²<sub>p</sub>": [
                "η²<sub>p</sub>"
            ],
            "η²p": [
                "η²p"
            ],
            "χ²": [
                "χ²"
            ],
            "χ² continuity correction": [
                "χ²-continuïteitscorrectie"
            ],
            "χ² Goodness of Fit": [
                "χ²-goodness-of-fit"
            ],
            "χ² Goodness of fit": [
                "χ²-goodness-of-fit"
            ],
            "χ² test": [
                "χ²-toets"
            ],
            "χ² test of association": [
                "χ²-associatietoets"
            ],
            "χ² Tests": [
                "χ²-toetsen"
            ],
            "ω²": [
                "ω²"
            ],
            "specific factor\u0004Factor": [
                "Factor"
            ]
        }
    },
    "code": "nl"
}