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endorse
View on CRAN: Click
here
Download and install endorse package within the R console
Install from CRAN:
install.packages("endorse")
Install from Github:
library("remotes")
install_github("cran/endorse")
Install by package version:
library("remotes")
install_version("endorse", "1.6.2")
Attach the package and use:
library("endorse")
Maintained by
Yuki Shiraito
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-01-16
Latest Update: 2022-05-02
Description:
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.
How to cite:
Yuki Shiraito (2012). endorse: Bayesian Measurement Models for Analyzing Endorsement Experiments. R package version 1.6.2, https://cran.r-project.org/web/packages/endorse. Accessed 07 Nov. 2024.
Previous versions and publish date:
1.0 (2012-01-16 23:17), 1.1 (2012-02-13 07:40), 1.2 (2012-02-25 21:54), 1.3.1 (2013-02-06 08:20), 1.3 (2013-01-24 11:49), 1.4.0 (2013-04-29 07:21), 1.4.1 (2014-05-04 07:40), 1.5.0 (2016-10-22 12:17), 1.5.1 (2017-03-20 01:04), 1.5.2 (2017-04-19 05:59), 1.6.0 (2017-06-25 17:31), 1.6.1 (2018-11-06 16:40)
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Functions, R codes and Examples using
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Some associated functions: GeoCount . GeoId . endorse . endorse.plot . pakistan . predict.endorse .
Some associated R codes: GeoCount.R . GeoID.R . endorse.R . endorse.plot.R . onAttach.R . Full endorse package functions and examples
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