endorse (1.5.1)

Bayesian Measurement Models for Analyzing Endorsement Experiments.


Fit the hierarchical and non-hierarchical Bayesian measurement models proposed by Bullock, Imai, and Shapiro (2011) 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.

Maintainer: Yuki Shiraito
Author(s): Yuki Shiraito [aut, cre], Kosuke Imai [aut], Bryn Rosenfeld [ctb]

License: GPL (>= 2)

Uses: coda

Released about 3 years ago.