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Framework for the Item Response Theory analysis of dichotomous and ordinal polytomous outcomes under the assumption of within-item multidimensionality and discreteness of the latent traits. The fitting algorithms allow for missing responses and for different item parametrizations and are based on the Expectation-Maximization paradigm. Individual covariates affecting the class weights may be included in the new version together with possibility of constraints on all model parameters.
Version: | 2.1.2 |
Depends: | R (≥ 2.0.0), MASS, limSolve, MultiLCIRT |
Published: | 2025-06-28 |
DOI: | 10.32614/CRAN.package.MLCIRTwithin |
Author: | Francesco Bartolucci [aut, cre], Silvia Bacci [aut] |
Maintainer: | Francesco Bartolucci <francesco.bartolucci at unipg.it> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
In views: | MissingData, Psychometrics |
CRAN checks: | MLCIRTwithin results |
Reference manual: | MLCIRTwithin.pdf |
Package source: | MLCIRTwithin_2.1.2.tar.gz |
Windows binaries: | r-devel: MLCIRTwithin_2.1.2.zip, r-release: MLCIRTwithin_2.1.2.zip, r-oldrel: MLCIRTwithin_2.1.2.zip |
macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): MLCIRTwithin_2.1.2.tgz, r-oldrel (x86_64): MLCIRTwithin_2.1.2.tgz |
Old sources: | MLCIRTwithin archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.