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Analysis of dichotomous and polytomous response data using unidimensional and multidimensional latent trait models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). 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 modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, and several other discrete latent variable models, including mixture and zero-inflated response models, are supported.

copied from cf-post-staging / r-mirt
Type Size Name Uploaded Downloads Labels
conda 2.0 MB | win-64/r-mirt-1.31-r36h796a38f_0.tar.bz2  6 years and 8 months ago 1360 main cf202003
conda 2.0 MB | win-64/r-mirt-1.31-r35h796a38f_0.tar.bz2  6 years and 8 months ago 1372 main cf202003
conda 1.9 MB | osx-64/r-mirt-1.31-r36hf99fc2c_0.tar.bz2  6 years and 8 months ago 385 main cf202003
conda 1.9 MB | osx-64/r-mirt-1.31-r35hf99fc2c_0.tar.bz2  6 years and 8 months ago 379 main cf202003
conda 1.9 MB | linux-64/r-mirt-1.31-r35h0357c0b_0.tar.bz2  6 years and 8 months ago 4641 main cf202003
conda 1.9 MB | linux-64/r-mirt-1.31-r36h0357c0b_0.tar.bz2  6 years and 8 months ago 4738 main cf202003

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