idealstan: Bayesian IRT Ideal Point Models with 'Stan'

Offers item-response theory (IRT) ideal-point scaling/dimension reduction methods that incorporate additional response categories and missing/censored values, including absences and abstentions, for roll call voting data (or any other kind of binary or ordinal item-response theory data). Full and approximate Bayesian inference is done via the 'Stan' engine (www.mc-stan.org).

Version: 0.2.7
Depends: R (≥ 3.1), Rcpp (≥ 0.12.7)
Imports: rstan (≥ 2.13.2), rstantools (≥ 1.1.0), methods (≥ 3.3.1), dplyr, tidyr, stringr, bayesplot, ggplot2, lazyeval, rlang, shinystan
LinkingTo: StanHeaders (≥ 2.13.1), rstan (≥ 2.13.2), BH (≥ 1.62.0.1), Rcpp (≥ 0.12.7), RcppEigen (≥ 0.3.2.9.0)
Suggests: pscl, loo, knitr, rmarkdown
Published: 2018-02-09
Author: Robert Kubinec [aut, cre], Jonah Gabry [ctb], Ben Goodrich [ctb], Trustees of Columbia University [cph]
Maintainer: Robert Kubinec <rmk7xy at virginia.edu>
BugReports: https://github.com/saudiwin/idealstan/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
SystemRequirements: GNU make
CRAN checks: idealstan results

Downloads:

Reference manual: idealstan.pdf
Vignettes: How to Evaluate Models
Introduction to Idealstan
Package source: idealstan_0.2.7.tar.gz
Windows binaries: r-prerel: idealstan_0.2.7.zip, r-release: idealstan_0.2.7.zip, r-oldrel: idealstan_0.2.7.zip
OS X binaries: r-prerel: idealstan_0.2.7.tgz, r-release: idealstan_0.2.7.tgz

Linking:

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