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.

AuthorJean-Paul Fox [aut], Konrad Klotzke [aut], Duco Veen [aut]
Date of publication2016-08-09 01:17:20
MaintainerKonrad Klotzke <omd.bms.utwente.stats@gmail.com>
LicenseGPL-2 | GPL-3
Version0.2.0

View on CRAN

Functions

getCellMeans Man page
getCellSizes Man page
getMLPrevalence Man page
getRRparameters Man page
getUniqueGroups Man page
hello Man page
intDotplot Man page
Plagiarism Man page
plot.RRglm Man page
plot.RRglmerMod Man page
print.RRglmGOF Man page
print.summary.RRglm Man page
print.summary.RRglmerMod Man page
residuals.RRglm Man page
residuals.RRglmerMod Man page
RRbinomial Man page
RRglm Man page
RRglmer Man page
RRglmGOF Man page
RRlink.cauchit Man page
RRlink.cloglog Man page
RRlink.logit Man page
RRlink.probit Man page
summary.RRglm Man page
summary.RRglmerMod Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.