Package: endorse 1.6.2

Yuki Shiraito

endorse: Bayesian Measurement Models for Analyzing Endorsement Experiments

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.

Authors:Yuki Shiraito [aut, cre], Kosuke Imai [aut], Bryn Rosenfeld [ctb]

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endorse.pdf |endorse.html✨
endorse/json (API)

Peer review:

Bug tracker:https://github.com/sensitivequestions/endorse/issues

On CRAN:

5 exports 3 stars 1.26 score 2 dependencies 3 scripts 308 downloads

Last updated 2 years agofrom:6ce3bd0749. Checks:OK: 9. Indexed: yes.

Exports:endorseendorse.plotGeoCountGeoIdpredict.endorse

Dependencies:codalattice