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.
|Depends:||R (≥ 2.0.0), MASS, limSolve, MultiLCIRT|
|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)]|
|CRAN checks:||MLCIRTwithin results|
|Windows binaries:||r-devel: MLCIRTwithin_2.1.zip, r-release: MLCIRTwithin_2.1.zip, r-oldrel: MLCIRTwithin_2.1.zip|
|OS X Mavericks binaries:||r-release: MLCIRTwithin_2.1.tgz, r-oldrel: MLCIRTwithin_2.1.tgz|
|Old sources:||MLCIRTwithin archive|
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