Abstract
Over the past few years, several studies have investigated and demonstrated the relationships between generalized linear mixed models (GLIMM) and item response modeling. Some benefits associated with this GLIMM-based modeling framework include the modeling of nested structure of data, such as examinees nested within schools (Kamata, 2001), of multidimensional measures (Cheong & Raudenbush, 2000), and of wider class of item response models, such as 2PL item response model (Rijmen et al., 2003).
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© 2007 Springer Science + Business Media, LLC
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Kamata, A., Cheong, Y.F. (2007). Multilevel Rasch Models. In: Multivariate and Mixture Distribution Rasch Models. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-0-387-49839-3_14
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DOI: https://doi.org/10.1007/978-0-387-49839-3_14
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