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.
- Version1.6.2
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release05/02/2022
Documentation
Team
Yuki Shiraito
Kosuke Imai
Bryn Rosenfeld
Show author detailsRolesContributor
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Last 30 days
This package has been downloaded 231 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 times.
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Last 365 days
This package has been downloaded 3,248 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Feb 12, 2025 with 49 downloads.
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Dependencies
- Depends1 package