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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: | 2.1.1 |
| Depends: | R (≥ 2.0.0), MASS, limSolve, MultiLCIRT |
| Published: | 2019-09-30 |
| Author: | Francesco Bartolucci, Silvia Bacci - University of Perugia (IT) |
| Maintainer: | Francesco Bartolucci <bart at stat.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_2.1.1.tar.gz |
| Windows binaries: | r-devel: MLCIRTwithin_2.1.1.zip, r-release: MLCIRTwithin_2.1.1.zip, r-oldrel: MLCIRTwithin_2.1.1.zip |
| macOS binaries: | r-release (arm64): MLCIRTwithin_2.1.1.tgz, r-oldrel (arm64): MLCIRTwithin_2.1.1.tgz, r-release (x86_64): MLCIRTwithin_2.1.1.tgz, r-oldrel (x86_64): MLCIRTwithin_2.1.1.tgz |
| Old sources: | MLCIRTwithin archive |
| Reverse suggests: | dextergui |
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