Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Multilevel IRT Modeling in Practice with the Package mlirt | Fox | Journal of Statistical Software
Authors: Jean-Paul Fox
Title: Multilevel IRT Modeling in Practice with the Package mlirt
Abstract: Variance component models are generally accepted for the analysis of hierarchical structured data. A shortcoming is that outcome variables are still treated as measured without an error. Unreliable variables produce biases in the estimates of the other model parameters. The variability of the relationships across groups and the group-effects on individuals' outcomes differ substantially when taking the measurement error in the dependent variable of the model into account. The multilevel model can be extended to handle measurement error using an item response theory (IRT) model, leading to a multilevel IRT model. This extended multilevel model is in particular suitable for the analysis of educational response data where students are nested in schools and schools are nested within cities/countries.

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Paper: Multilevel IRT Modeling in Practice with the Package mlirt     Download PDF (Downloads: 12582)
Supplements: Data sets in SPSS format Download (Downloads: 2934; 1MB)
mlirt_1.0.tar.gz: R source package Download (Downloads: 3073; 682KB) v20i05.R: R example code from the paper Download (Downloads: 2904; 2KB)

DOI: 10.18637/jss.v020.i05

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Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.