GLMMRR: 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.

Version: 0.2.0
Depends: lme4, methods
Imports: lattice, stats, utils, grDevices
Published: 2016-08-09
Author: Jean-Paul Fox [aut], Konrad Klotzke [aut], Duco Veen [aut]
Maintainer: Konrad Klotzke <omd.bms.utwente.stats at gmail.com>
License: GPL-2 | GPL-3
NeedsCompilation: no
CRAN checks: GLMMRR results

Downloads:

Reference manual: GLMMRR.pdf
Package source: GLMMRR_0.2.0.tar.gz
Windows binaries: r-devel: GLMMRR_0.2.0.zip, r-release: GLMMRR_0.2.0.zip, r-oldrel: GLMMRR_0.2.0.zip
OS X binaries: r-release: GLMMRR_0.2.0.tgz, r-oldrel: GLMMRR_0.2.0.tgz
Old sources: GLMMRR archive

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