Nothing
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.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Phil 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] |
| Maintainer | Phil Chalmers <rphilip.chalmers@gmail.com> |
| License | GPL (>= 3) |
| Version | 1.42 |
| URL | https://github.com/philchalmers/mirt https://github.com/philchalmers/mirt/wiki https://groups.google.com/forum/#!forum/mirt-package |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the mirt package in your browser
Any scripts or data that you put into this service are public.
