Package: endorse
Version: 1.6.2
Date: 2022-5-2
Title: Bayesian Measurement Models for Analyzing Endorsement
        Experiments
Authors@R: c(person("Yuki", "Shiraito", role = c("aut","cre"), email = "shiraito@umich.edu"),
	     person("Kosuke", "Imai", role = "aut", email = "imai@harvard.edu"),
	     person("Bryn", "Rosenfeld", role = "ctb", email = "brosenfe@usc.edu"))
Author: Yuki Shiraito [aut, cre], Kosuke Imai [aut], Bryn Rosenfeld
        [ctb]
Maintainer: Yuki Shiraito <shiraito@umich.edu>
Depends: coda, utils
Description: Fit the hierarchical and non-hierarchical Bayesian
        measurement models proposed by Bullock, Imai, and Shapiro
        (2011) <DOI:10.1093/pan/mpr031> to analyze endorsement
        experiments.  Endorsement experiments are a survey methodology
        for eliciting truthful responses to sensitive questions.  This
        methodology is helpful when measuring support for socially
        sensitive political actors such as militant groups.  The model
        is fitted with a Markov chain Monte Carlo algorithm and
        produces the output containing draws from the posterior
        distribution.
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)
URL: https://github.com/SensitiveQuestions/endorse/
NeedsCompilation: yes
Packaged: 2026-10-12 10:51:59 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2022-05-02 06:00:12 UTC
RemoteUrl: https://github.com/cran/endorse
RemoteRef: HEAD
RemoteSha: 9f80302170d718dec3d263eefedd5e50e024d68a