Asymmetric Item Characteristic Curves and Item Complexity: Insights from Simulation and Real Data Analyses

Sora Lee () and Daniel M. Bolt ()
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Sora Lee: University of Wisconsin
Daniel M. Bolt: University of Wisconsin

Psychometrika, 2018, vol. 83, issue 2, No 11, 453-475

Abstract: Abstract While item complexity is often considered as an item feature in test development, it is much less frequently attended to in the psychometric modeling of test items. Prior work suggests that item complexity may manifest through asymmetry in item characteristics curves (ICCs; Samejima in Psychometrika 65:319–335, 2000). In the current paper, we study the potential for asymmetric IRT models to inform empirically about underlying item complexity, and thus the potential value of asymmetric models as tools for item validation. Both simulation and real data studies are presented. Some psychometric consequences of ignoring asymmetry, as well as potential strategies for more effective estimation of asymmetry, are considered in discussion.

Keywords: item response theory; asymmetric item characteristic curves; item complexity; item validation (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11336-017-9586-5

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