Noncompensatory MIRT For Passage-Based Tests

Nana Kim (), Daniel M. Bolt and James Wollack
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Nana Kim: University of Wisconsin-Madison
Daniel M. Bolt: University of Wisconsin-Madison
James Wollack: University of Wisconsin-Madison

Psychometrika, 2022, vol. 87, issue 3, No 8, 992-1009

Abstract: Abstract We consider a multidimensional noncompensatory approach for binary items in passage-based tests. The passage-based noncompensatory model (PB-NM) emphasizes two underlying components in solving passage-based test items: a passage-related component and a passage-independent component. An advantage of the PB-NM model over commonly applied compensatory models (e.g., bifactor model) is that the two components are parameterized in relation to difficulty as opposed to discrimination parameters. As a result, while simultaneously accounting for passage-related local item dependence, the model permits the assessment of how items based on the same passage may require varying levels of passage comprehension (as well as varying levels of passage-independent proficiency) to obtain a correct response. Through a simulation study, we evaluate the comparative fit of the PB-NM against the bifactor model and also illustrate the relationship between the difficulty parameters of the PB-NM and the discrimination parameters of the bifactor model. We further apply the PB-NM to an actual reading comprehension test to demonstrate the relevance of the model in understanding variation in the relative difficulty of the two components across different item types.

Keywords: multidimensional item response theory (MIRT); noncompensatory MIRT; conjunctive Rasch model; bifactor model; passage-based tests (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11336-021-09826-6

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