Graeme Blair <graeme.blair@columbia.edu>, Yang-Yang Zhou
<yz3@princeton.edu>, Kosuke Imai <kimai@princeton.edu>
Enables researchers to conduct multivariate statistical analyses
of survey data with randomized response technique items from several designs,
including mirrored question, forced question, and unrelated question. This
includes regression with the randomized response as the outcome and logistic
regression with the randomized response item as a predictor. In addition,
tools for conducting power analysis for designing randomized response items
are included. The package implements methods described in Blair, Imai, and Zhou
(2015) ''Design and Analysis of the Randomized Response Technique,'' Working
paper available at <http://graemeblair.com/papers/randresp.pdf>.

c(person("Graeme", "Blair", email = "graeme.blair@gmail.com", role = c("aut", "cre")),
person("Yang-Yang", "Zhou", email = "yangyang.zhou@ubc.ca", role = c("aut")),
person("Kosuke", "Imai", email = "imai@harvard.edu", role = c("aut")),
person("Winston", "Chou", email = "wchou@princeton.edu", role = c("ctb")))
Enables researchers to conduct multivariate statistical analyses
of survey data with randomized response technique items from several designs,
including mirrored question, forced question, and unrelated question. This
includes regression with the randomized response as the outcome and logistic
regression with the randomized response item as a predictor. In addition,
tools for conducting power analysis for designing randomized response items
are included. The package implements methods described in Blair, Imai, and Zhou
(2015) ''Design and Analysis of the Randomized Response Technique,'' Journal
of the American Statistical Association
<https://graemeblair.com/papers/randresp.pdf>.
Graeme Blair [aut, cre],
Yang-Yang Zhou [aut],
Kosuke Imai [aut],
Winston Chou [ctb]

Graeme Blair [aut, cre], Yang-Yang Zhou [aut, cre],
Kosuke Imai [aut, cre], Winston Chou [ctb]
Enables researchers to conduct multivariate statistical analyses
of survey data with randomized response technique items from several designs,
including mirrored question, forced question, and unrelated question. This
includes regression with the randomized response as the outcome and logistic
regression with the randomized response item as a predictor. In addition,
tools for conducting power analysis for designing randomized response items
are included. The package implements methods described in Blair, Imai, and Zhou
(2015) ''Design and Analysis of the Randomized Response Technique,'' Journal
of the American Statistical Association
<http://graemeblair.com/papers/randresp.pdf>.