Bayesian Measurement Models for Analyzing Endorsement Experiments
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 6
- Examples that run
- 50%1 run in a plain check · 1 never run
- Exported functions with examples
- 40%
- Documented parameters
- 100%
- Return-value docs
- 80%
- Help pages citing references
- 33%
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- not measured
- Median days to close, 50 most recently updated closed PRs
- 7
Stars over time
PRs over time
3 development-tooling and community-health practices detected across 2 families in the upstream repository
Checks run against github.com/sensitivequestions/endorse on 2026-10-22.
GitHub Pages site last deployed 2022-05-02
Dependencies
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.6.2Latest
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 1.6.12018-11-06 · diff ↗
- RR 3.5.0 released · 2018-04-23
- 1.6.0
- RR 3.4.0 released · 2017-04-21
- 1.5.22017-04-19 · diff ↗
- 1.5.12017-03-20 · diff ↗
- 1.5.02016-10-22 · diff ↗
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Package metadata
- First published
- 2012-01-16
- Total releases
- 13 / 14 yrs
- License
- GPL (>= 2) OSI
- Bundled data
- 51 KB / 1 file
- Download size
- 93 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("endorse")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
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