oddsratio              package:epitools              R Documentation

_O_d_d_s _r_a_t_i_o _e_s_t_i_m_a_t_i_o_n _a_n_d _c_o_n_f_i_d_e_n_c_e _i_n_t_e_r_v_a_l_s

_D_e_s_c_r_i_p_t_i_o_n:

     Calculates odds ratio by median-unbiased estimation (mid-p),
     conditional maximum likelihood estimation (Fisher), unconditional
     maximum likelihood estimation (Wald), and small sample adjustment
     (small). Confidence intervals are calculated using exact methods
     (mid-p and Fisher), normal approximation (Wald), and normal
     approximation with small sample adjustment (small).

_U_s_a_g_e:

     oddsratio(x, y = NULL,
               method = c("midp", "fisher", "wald", "small"),
               conf.level = 0.95,
               rev = c("neither", "rows", "columns", "both"),
               correction = FALSE,
               verbose = FALSE)
     oddsratio.midp(x, y = NULL,
                    conf.level = 0.95,
                    rev = c("neither", "rows", "columns", "both"),
                    correction = FALSE,
                    verbose = FALSE,
                    interval =  c(0, 1000))
     oddsratio.fisher(x, y = NULL,
                      conf.level = 0.95,
                      rev = c("neither", "rows", "columns", "both"),
                      correction = FALSE,
                      verbose = FALSE)
     oddsratio.wald(x, y = NULL,
                    conf.level = 0.95,
                    rev = c("neither", "rows", "columns", "both"),
                    correction = FALSE,
                    verbose = FALSE)
     oddsratio.small(x, y = NULL,
                     conf.level = 0.95,
                     rev = c("neither", "rows", "columns", "both"),
                     correction = FALSE,
                     verbose = FALSE)

_A_r_g_u_m_e_n_t_s:

       x: input data can be one of the following: r x 2 table, vector
          of numbers from a contigency table (will be transformed into
          r x 2 table in row-wise order), or single factor or character
          vector that will be combined with 'y' into a table.

       y: single factor or character vector that will be combined with
          'x' into a table (default is NULL) 

  method: method for calculating odds ratio and confidence interval 

conf.level: confidence level (default is 0.95)

     rev: reverse order of "rows", "colums", "both", or "neither"
          (default) 

correction: set to TRUE for Yate's continuity correction (default is
          FALSE) 

 verbose: set to TRUE to return more detailed results (default is
          FALSE) 

interval: interval for the 'uniroot' that finds the odds ratio
          median-unbiased estimate and mid-p exact confidence interval
          for 'oddsratio.midp' 

     ...: passes optional arguments to 'tab2by2.test' for calculatng
          tests of independence (p values): adding 'correction = TRUE'
          implements Yate's continuity correction (default is FALSE),
          and adding 'replicates = n' where 'n' is an integer
          specifying the number of iterations (default is 2000) of the
          Monte Carlo simulation method of calculating p values.  

_D_e_t_a_i_l_s:

     Calculates odds ratio by median-unbiased estimation (mid-p),
     conditional maximum likelihood estimation (Fisher), unconditional
     maximum likelihood estimation (Wald), and small sample adjustment
     (small). Confidence intervals are calculated using  exact methods
     (mid-p and Fisher), normal approximation (Wald), and normal
     approximation with small sample adjustment (small). 

     This function expects the following table struture:


                         disease=0   disease=1
         exposed=0 (ref)    n00         n01
         exposed=1          n10         n11  
         exposed=2          n20         n21
         exposed=3          n30         n31

     The reason for this is because each level of exposure is compared
     to the reference level.

     If you are providing a 2x2 table the following table is preferred:


                         disease=0   disease=1
         exposed=0 (ref)    n00         n01
         exposed=1          n10         n11  

     however, for odds ratios from 2x2 tables, the following table is
     equivalent:


                         disease=1   disease=0
         exposed=1          n11         n10
         exposed=0          n01         n00  

     If the table you want to provide to this function is not in the
     preferred form, just use the 'rev' option to "reverse" the rows,
     columns, or both. If you are providing categorical variables
     (factors or character vectors), the first level of the "exposure"
     variable is treated as the reference. However, you can set the
     reference of a factor using the 'relevel' function.

     Likewise, each row of the rx2 table is compared to the exposure
     reference level and test of independence two-sided p values are
     calculated using mid-p exact, Fisher's Exact, Monte Carlo
     simulation, and the chi-square test.

_V_a_l_u_e:

       x: table that was used in analysis (verbose = TRUE)

    data: same table as 'x' but with marginal totals

p.exposed: proportions exposed (verbose = TRUE)

p.outcome: proportions experienced outcome (verbose = TRUE)

 measure: risk ratio and confidence interval

conf.level: confidence level used (verbose = TRUE)

 p.value: p value for test of independence

replicates: number of replicates used in Monte Carlo simulation p value
          (verbose = TRUE)

correction: logical specifying if continuity correction was used

_N_o_t_e:

     Visit <URL: http://www.epitools.net> for the latest.

_A_u_t_h_o_r(_s):

     Tomas Aragon, aragon@berkeley.edu, <URL: http://www.medepi.com>

_R_e_f_e_r_e_n_c_e_s:

     Kenneth J. Rothman and Sander Greenland (1998), Modern
     Epidemiology, Lippincott-Raven Publishers

     Kenneth J. Rothman (2002), Epidemiology: An Introduction, Oxford
     University Press

     Nicolas P. Jewell (2004), Statistics for Epidemiology, 1st
     Edition, 2004, Chapman & Hall, pp. 73-81

_S_e_e _A_l_s_o:

     'tab2by2.test', 'riskratio', 'rateratio', 'ormidp.test', 'epitab'

_E_x_a_m_p_l_e_s:

     ##Case-control study assessing whether exposure to tap water
     ##is associated with cryptosporidiosis among AIDS patients

     tapw <- c("Lowest", "Intermediate", "Highest")
     outc <- c("Case", "Control")    
     dat <- matrix(c(2, 29, 35, 64, 12, 6),3,2,byrow=TRUE)
     dimnames(dat) <- list("Tap water exposure" = tapw, "Outcome" = outc)
     oddsratio(dat, rev="c")
     oddsratio.midp(dat, rev="c")
     oddsratio.fisher(dat, rev="c")
     oddsratio.wald(dat, rev="c")
     oddsratio.small(dat, rev="c")

