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, and zero-inflated response models are supported.
| Version: |
1.41 |
| Depends: |
stats, R (≥ 3.6.0), stats4, lattice, methods |
| Imports: |
GPArotation, gridExtra, Matrix (≥ 1.5-0), Rcpp, mgcv, vegan, Deriv, splines, pbapply (≥ 1.3-0), dcurver |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
boot, latticeExtra, directlabels, shiny, knitr, markdown, Rsolnp, nloptr, sirt, plink, mirtCAT |
| Published: |
2023-10-17 |
| Author: |
Phil Chalmers 
[aut, cre],
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 at gmail.com> |
| BugReports: |
https://github.com/philchalmers/mirt/issues?state=open |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/philchalmers/mirt,
https://github.com/philchalmers/mirt/wiki,
https://groups.google.com/forum/#!forum/mirt-package |
| NeedsCompilation: |
yes |
| Citation: |
mirt citation info |
| Materials: |
README NEWS |
| In views: |
MissingData, Psychometrics |
| CRAN checks: |
mirt results |