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Category: Project

Description: This study proposes a novel method for estimating respondents’ abilities using item response theory (IRT) models with dichotomous or polytomous items. The proposed technique extends the expected a posteriori (EAP) estimation method (Bock & Aitkin, 1981) by incorporating a standardized weight function based on either user-defined values or item-fit statistics. The standardized weight values range from 0 to 1, where responses from items with lower weight values contribute less to the ability estimates. A Monte Carlo simulation was used to evaluate the new item-weighted expected a posteriori (IWEAP) approach and compare it to the common ability estimation techniques. Simulation conditions include various IRT models, the number of items, the number of response options, and the type of item-fit statistics. Results from the simulation show that the novel IWEAP approach offers more precise ability estimates which are robust to poor item fit and misspecification. Recommendations for using IWEAP in research and applied settings will be discussed. We further offer additional insights about user-generated weights and when these should be preferred over item-fit statistics.