Title: Correlation and Regression Analyses for Randomized Response Data
Description: RRreg provides 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 and as
predictors in a linear regression. For simulation and bootstrap purposes,
RR data can be generated according to several models.

Description: Univariate and multivariate methods to analyze

Imports: parallel, doParallel, foreach, stats, grDevices, graphics

Imports: parallel, doParallel, foreach, stats, grDevices, graphics,
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.

Description: 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.

Description: 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>