Packaged: 2020-11-10 16:37:02 UTC; gconverse

Title: Latent Class Item Response Theory Models Under 'Within-Item
Author: Francesco Bartolucci, Silvia Bacci - University of Perugia (IT)
Description: Framework for the Item Response Theory analysis of dichotomous and ordinal polytomous outcomes under the assumption of within-item multi-dimensionality and discreteness of the latent traits. The fitting algorithms allow for missing responses and for different item parameterizations and are based on the Expectation-Maximization paradigm. Individual covariates affecting the class weights may be included in the new version.
Depends: R (>= 2.0.0), MASS, limSolve, MultiLCIRT
Packaged: 2015-06-02 18:01:13 UTC; francescobartolucci

Title: Latent Class Item Response Theory (LC-IRT) Models under
Description: 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.
Packaged: 2016-02-03 17:55:44 UTC; francesco

Description: 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.
Packaged: 2016-07-20 09:10:40 UTC; francescobartolucci

Packaged: 2019-09-30 12:50:50 UTC; francescobartolucci

Packaged: 2016-08-04 15:49:18 UTC; francescobartolucci

Title: Maximum Likelihood Conjoint Measurement
Author: Kenneth Knoblauch and Laurence T. Maloney
Depends: R (>= 2.9), graphics, stats, utils, base
Description: Conjoint measurement is a psychophysical procedure in
which stimulus pairs are presented that vary along n > 2
dimensions and the observer is required to compare the stimuli
along one of them.  This package contains functions to estimate
the contribution of the n scales to the judgment by a maximum
likelihood method under several hypotheses of how the
Packaged: 2009-09-08 20:25:51 UTC; knoblauch