RRreg: Correlation and Regression Analyses for Randomized Response Data

Univariate and multivariate methods to analyze randomized response (RR) survey designs (e.g., Warner, S. L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63–69). <doi:10.2307/2283137> Besides univariate estimates of true proportions, RR variables can be used for correlations, as dependent variable in a logistic regression (with or without random effects), as predictors in a linear regression, or as dependent variable in a beta-binomial ANOVA. For simulation and bootstrap purposes, RR data can be generated according to several models.

Version: 0.6.2
Depends: R (≥ 3.0.0)
Imports: parallel, doParallel, foreach, stats, grDevices, graphics, lme4
Suggests: knitr
Published: 2017-03-08
Author: Daniel W. Heck [aut, cre], Morten Moshagen [aut]
Maintainer: Daniel W. Heck <heck at uni-mannheim.de>
License: GPL-2
URL: http://psycho3.uni-mannheim.de/Home/Research/Software/RRreg/
NeedsCompilation: no
Citation: RRreg citation info
Materials: NEWS
CRAN checks: RRreg results


Reference manual: RRreg.pdf
Vignettes: An Introduction to the RRreg package
Package source: RRreg_0.6.2.tar.gz
Windows binaries: r-devel: RRreg_0.6.2.zip, r-release: RRreg_0.6.2.zip, r-oldrel: RRreg_0.6.2.zip
OS X El Capitan binaries: r-release: RRreg_0.6.2.tgz
OS X Mavericks binaries: r-oldrel: RRreg_0.6.2.tgz
Old sources: RRreg archive


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