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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.6.2 |
rolling source/ R- | endorse_1.6.2.tar.gz |
92.1 KiB |
1.6.2 |
latest source/ R- | endorse_1.6.2.tar.gz |
92.1 KiB |
1.6.2 |
2026-04-09 windows/windows R-4.5 | endorse_1.6.2.zip |
179.2 KiB |