RRreg-package: Correlation and Regression Analyses for Randomized Response...

In danheck/RRreg: Correlation and Regression Analyses for Randomized Response Data

Correlation and Regression Analyses for Randomized Response Designs

Description

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').

Details

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

Citation

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

Author(s)

Daniel W. Heck [e-mail]

References

Warner, S. L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63–69.

See Also

Useful links:

• https://github.com/danheck/RRreg

danheck/RRreg documentation built on Dec. 3, 2022, 7:50 p.m.