Analysis of dichotomous and polytomous response data using
unidimensional and multidimensional latent trait models under the Item
Response Theory paradigm. Exploratory and confirmatory models can be
estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory
bi-factor and two-tier analyses are available for modeling item testlets.
Multiple group analysis and mixed effects designs also are available for
detecting differential item and test functioning as well as modelling
item and person covariates. Finally, latent class models such as the DINA,
DINO, multidimensional latent class, and several other discrete latent
variable models are supported.
| Version: |
1.25 |
| Depends: |
stats, R (≥ 3.1.0), stats4, lattice, methods |
| Imports: |
GPArotation, Rcpp, sfsmisc, mgcv, splines, numDeriv |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
boot, latticeExtra, directlabels, shiny, knitr, Rsolnp, nloptr, sirt, mirtCAT |
| Published: |
2017-07-23 |
| Author: |
Phil Chalmers [aut, cre, cph],
Joshua Pritikin [ctb],
Alexander Robitzsch [ctb],
Mateusz Zoltak [ctb],
KwonHyun Kim [ctb],
Carl F. Falk [ctb],
Adam Meade [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: |
Psychometrics |
| CRAN checks: |
mirt results |