Generalized Linear Mixed Model (GLMM) for Binary Randomized Response Data

Generalized Linear Mixed Model (GLMM) for Binary Randomized Response Data. Includes Cauchit, Compl. Log-Log, Logistic, and Probit link functions for Bernoulli Distributed RR data. RR Designs: Warner, Forced Response, Unrelated Question, Kuk, Crosswise, and Triangular. Reference: Fox, J-P, Veen, D. and Klotzke, K. (2018). Generalized Linear Mixed Models for Randomized Responses. Methodology. .


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("GLMMRR")

0.5.0 by Konrad Klotzke, 10 days ago


Browse source code at https://github.com/cran/GLMMRR


Authors: Jean-Paul Fox [aut] , Konrad Klotzke [aut] , Duco Veen [aut]


Documentation:   PDF Manual  


Task views: Psychometric Models and Methods


GPL-3 license


Imports lattice, stats, utils, grDevices, RColorBrewer

Depends on lme4, methods


See at CRAN