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). 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: 0.6.1
Depends: R (≥ 3.0.0)
Imports: parallel, doParallel, foreach, stats, grDevices, graphics, lme4
Suggests: knitr
Published: 2016-01-12
Author: Daniel W. Heck [aut, cre], Morten Moshagen [aut]
Maintainer: Daniel W. Heck <dheck at mail.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_0.6.1.tar.gz
Windows binaries: r-devel: RRreg_0.6.1.zip, r-release: RRreg_0.6.1.zip, r-oldrel: RRreg_0.6.1.zip
OS X Snow Leopard binaries: r-release: RRreg_0.6.1.tgz, r-oldrel: RRreg_0.3.0.tgz
OS X Mavericks binaries: r-release: RRreg_0.6.1.tgz
Old sources: RRreg archive