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Authors: Jean-Paul Fox
Title: [download]
(9426)
Multilevel IRT Modeling in Practice with the Package mlirt
Reference: Vol. 20, Issue 5, Feb 2007
Submitted 2006-10-01, Accepted 2007-02-22
Type: Article
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.

Paper: [download]
(9426)
Multilevel IRT Modeling in Practice with the Package mlirt
(application/pdf, 309.5 KB)
Supplements: [download]
(2550)
Data.zip: Data sets in SPSS format
(application/zip, 2 MB)
[download]
(2640)
mlirt_1.0.tar.gz: R source package
(application/x-gzip, 682.5 KB)
[download]
(2503)
v20i05.R: R example code from the paper
(application/zip, 2 KB)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
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