rr implements methods developed by Blair, Imai, and Zhou (2015) such as multivariate regression and power analysis for the randomized response technique. Randomized response is a survey technique that introduces random noise to reduce potential bias from non-response and social desirability when asking questions about sensitive behaviors and beliefs. The current version of this package conducts multivariate regression analyses for the sensitive item under four standard randomized response designs: mirrored question, forced response, disguised response, and unrelated question. Second, it generates predicted probabilities of answering affirmatively to the sensitive item for each respondent. Third, it also allows users to use the sensitive item as a predictor in an outcome regression under the forced response design. Additionally, it implements power analyses to help improve research design. In future versions, this package will extend to new modified designs that are based on less stringent assumptions than those of the standard designs, specifically to allow for non-compliance and unknown distribution to the unrelated question under the unrelated question design.

## Details

 Package: rr Type: Package Version: 1.2 Date: 2015-3-8 License: GPL (>= 2)

## References

Blair, Graeme, Kosuke Imai and Yang-Yang Zhou. (2015) "Design and Analysis of the Randomized Response Technique." Journal of the American Statistical Association. Available at http://graemeblair.com/papers/randresp.pdf.