Univariate and multivariate methods for randomized response (RR) survey designs (e.g., Warner, 1965). Univariate estimates of true proportions can be obtained using
RRuni. RR variables can be used in multivariate analyses for correlations (
RRcor), as dependent variable in a logistic regression (
RRlog), or as predictors in a linear regression (
RRlin). The function
RRgen generates single RR data sets, whereas
RRsimu generates and analyzes RR data repeatedly for simulation and bootstrap purposes. An overview of the available RR designs and examples can be found in the package vignette by
|Depends:||R (>= 3.0.0)|
|Imports:||parallel, doParallel, foreach, stats, grDevices, graphics, lme4|
If you use
RRreg in publications, please cite the package as follows:
Heck, D. W., & Moshagen, M. (2018). RRreg: An R package for correlation and regression analyses of randomized response data. Journal of Statistical Software. 85 (2), 1-29. doi: 10.18637/jss.v085.i02
Warner, S. L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63–69.
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