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]

endorse_1.6.2.tar.gz
endorse_1.6.2.tar.gz(r-4.5-noble)endorse_1.6.2.tar.gz(r-4.4-noble)
endorse_1.6.2.tgz(r-4.4-emscripten)endorse_1.6.2.tgz(r-4.3-emscripten)
endorse.pdf |endorse.html
endorse/json (API)

# Install 'endorse' in R:
install.packages('endorse', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

Uses libs:
  • openblas– Optimized BLAS
Datasets:
  • pakistan - Pakistan Survey Experiment on Support for Militant Groups

openblas

1.70 score 222 downloads 5 exports 2 dependencies

Last updated 3 years agofrom:9f80302170. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 10 2024
R-4.5-linux-x86_64OKDec 10 2024

Exports:endorseendorse.plotGeoCountGeoIdpredict.endorse

Dependencies:codalattice