GLMMRR: Generalized Linear Mixed Model (GLMM) for Binary RandomizedResponse 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. <doi:10.1027/1614-2241/a000153>.
| Version: | 0.6.0 |
| Depends: | R (≥ 3.5.0),lme4, methods |
| Imports: | lattice, stats, utils, grDevices,RColorBrewer |
| Published: | 2025-09-18 |
| DOI: | 10.32614/CRAN.package.GLMMRR |
| Author: | Jean-Paul Fox [aut, cre], Konrad Klotzke [aut], Duco Veen [aut] |
| Maintainer: | Jean-Paul Fox <jpfox00 at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| In views: | MixedModels,Psychometrics |
| CRAN checks: | GLMMRR results |
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