Abstract
Cluster-speci_c item e_ects parameters are introduced that are assumed to vary over clusters of respondents. The modeling of cluster-speci_c item parameters relaxes the assumptions of measurement invariance. Item characteristic di_erences are simply allowed, and it is not necessary to classify items as being invariant or noninvariant. Tests and estimation methods are discussed for item response models with random item e_ects parameters.
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© 2010 Springer New York
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Fox, JP. (2010). Random Item Effects Models. In: Bayesian Item Response Modeling. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0742-4_7
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DOI: https://doi.org/10.1007/978-1-4419-0742-4_7
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-0741-7
Online ISBN: 978-1-4419-0742-4
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