RRreg-package | R Documentation |

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
`vignette('RRreg')`

.

In case of issues or questions, please refer to the GitHub repository: https://github.com/danheck/RRreg

An introduction with examples is available via `vignette("RRreg")`

or
at the website: https://www.dwheck.de/vignettes/RRreg.html

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

Daniel W. Heck daniel.heck@uni-marburg.de

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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