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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: | 0.5.0 |
Depends: | R (≥ 3.5.0), lme4, methods |
Imports: | lattice, stats, utils, grDevices, RColorBrewer |
Published: | 2021-01-13 |
DOI: | 10.32614/CRAN.package.GLMMRR |
Author: | Jean-Paul Fox [aut], Konrad Klotzke [aut], Duco Veen [aut] |
Maintainer: | Konrad Klotzke <omd.bms.utwente.stats at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | no |
In views: | MixedModels, Psychometrics |
CRAN checks: | GLMMRR results |
Reference manual: | GLMMRR.pdf |
Package source: | GLMMRR_0.5.0.tar.gz |
Windows binaries: | r-devel: GLMMRR_0.5.0.zip, r-release: GLMMRR_0.5.0.zip, r-oldrel: GLMMRR_0.5.0.zip |
macOS binaries: | r-release (arm64): GLMMRR_0.5.0.tgz, r-oldrel (arm64): GLMMRR_0.5.0.tgz, r-release (x86_64): GLMMRR_0.5.0.tgz, r-oldrel (x86_64): GLMMRR_0.5.0.tgz |
Old sources: | GLMMRR archive |
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