R: Rank-Based Estimation and Prediction in Random Effects Nested Models

# Rank-Based Estimation and Prediction in Random Effects Nested Models

## Documentation for package ‘rlme’ version 0.5

- DESCRIPTION file.
- Package NEWS.

## Help Pages

rlme-package | rlme
beta_var | Estimate fixed-effect variance for Joint Rank Method (JR) in three-level nested design.
compare.fits | Compare Fits
dispvar | Rank-based dispersion estimate.
fitdvcov | Fitdvcov
GEER_est | GEER: General Estimating Equation Rank-Based Estimation Method
getgrstplot | Q-Q Plot and Standardized Residual Plot for the GR fit.
getlmestplot | Q-Q Plot and Standardized Residual Plot for the REML or ML fit.
GR_est | GR Method
hbrwts_gr | HBR Weight
instruction | Instruction
JR_est | JR Method
lmr | Rank Based Fixed Effect Regression
LM_est | Linear Model Estimation using the nlme package.
minimize_dispersion | Minimize Dispersion Function
plot.rlme | Plot rlme Fit
rhosch | Cluster Correlation Coefficient Estimate
rhosect | Subcluster Correlation Coefficient Estimate
rlme | Rank-based Estimates for Mixed-Effects Nested Models
rpr | Cluster and Subcluster effects
rprmeddis | Rprmeddis
schools | PISA Literacy Data
stanresidgr | Calculate Standard Residuals
summary.rlme | rlme Summary
wilonestep | Wilcoxon estimate for independent linear models
wilstep | Wilcoxon One Step Rank-based Estimate in GR Method