jdcc/emirt

emIRT: EM Algorithms for Estimating Item Response Theory Models

emIRT: EM Algorithms for Estimating Item Response Theory Models

Various Expectation-Maximization (EM) algorithms are implemented for item response theory (IRT) models. The current implementation includes IRT models for binary and ordinal responses, along with dynamic and hierarchical IRT models with binary responses. Variational algorithms for scaling network and text data are also included. The details about the methods implemented in this package are described in Imai, Lo, and Olmsted. (2016). "Fast Estimation of Ideal Points with Massive Data." American Political Science Review, Vol. 110, No. 4 (December), pp. 631-656.

The current release of the R package is available on CRAN.

The github versions of the R package are available with

library("devtools")
install_github("kosukeimai/emIRT")
install_github("kosukeimai/emIRT", ref ="development")