mirt: Multidimensional Item Response Theory

Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported.

Package details

AuthorPhil Chalmers [aut, cre] (<https://orcid.org/0000-0001-5332-2810>), Joshua Pritikin [ctb], Alexander Robitzsch [ctb], Mateusz Zoltak [ctb], KwonHyun Kim [ctb], Carl F. Falk [ctb], Adam Meade [ctb], Lennart Schneider [ctb], David King [ctb], Chen-Wei Liu [ctb], Ogreden Oguzhan [ctb]
MaintainerPhil Chalmers <rphilip.chalmers@gmail.com>
LicenseGPL (>= 3)
Version1.42
URL https://github.com/philchalmers/mirt https://github.com/philchalmers/mirt/wiki https://groups.google.com/forum/#!forum/mirt-package
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("mirt")

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mirt documentation built on Sept. 11, 2024, 7:14 p.m.