developed by Imai (2011) and Blair and Imai (2012), a Bayesian
MCMC implementation of regression for the standard and multiple
sensitive item list experiment designs including ceiling and
floor effects and a random effects setup, and a Bayesian MCMC
hierarchical regression model with up to three hierarchical

developed by Imai (2011), Blair and Imai (2012), and Blair,
Imai, and Lyall (2013). This includes a Bayesian MCMC
implementation of regression for the standard and multiple
sensitive item list experiment designs and a random effects
setup, a Bayesian MCMC hierarchical regression model with up to
three hierarchical groups, and the combined list experiment and

developed by Imai (2011), Blair and Imai (2012), Blair,
Imai, and Lyall (2013), and Imai, Park, and Greene (2014).
This includes a Bayesian MCMC implementation of regression
for the standard and multiple sensitive item list experiment
designs and a random effects setup, a Bayesian MCMC hierarchical
regression model with up to three hierarchical groups, the
combined list experiment and endorsement experiment regression
model, and a joint model of the list experiment that enables
the analysis of the list experiment as a predictor in

Author: Graeme Blair [aut, cre], Kosuke Imai [aut, cre], Bethany Park [ctb],
Depends: R (>= 3.2.0), utils, sandwich (>= 2.3-3)
Suggests: testthat (>= 0.9.1), knitr (>= 1.10.5)
Description: Allows researchers to conduct multivariate statistical analyses of survey data with list experiments. This survey methodology is also known as the item count technique or the unmatched count technique and is an alternative to the commonly used randomized response method. The package implements the methods developed by Imai (2011), Blair and Imai (2012), Blair, Imai, and Lyall (2013), Imai, Park, and Greene (2014), and Aronow, Coppock, Crawford, and Green (2015). This includes a Bayesian MCMC implementation of regression for the standard and multiple sensitive item list experiment designs and a random effects setup, a Bayesian MCMC hierarchical regression model with up to three hierarchical groups, the combined list experiment and endorsement experiment regression model, a joint model of the list experiment that enables the analysis of the list experiment as a predictor in outcome regression models, and a method for combining list experiments with direct questions. In addition, the package implements the statistical test that is designed to detect certain failures of list experiments, and a placebo test for the list experiment using data from direct questions.