Assessment of Testlet Effects: Testing it All at Once

A testlet is a cluster of items that shares a common stimulus (e.g., a set of questions all related to the same text passage). Testlets are commonly used in educational and psychological assessments for their appealing features regarding test development and administration. Yet, bundling items into testlets calls into question one of the key statistical assumptions underlying any assessment: local independence of the test item responses. This article presents a condensed version of (Lim, 2024), which proposed a new index—the parametric bootstrap Mantel–Haenszel \(\text{MH} \chi ^2_{testlet}\) —as a device for detecting the presence of testlet effects at the level of an entire testlet and not just for pairs of items. The description of the theoretical foundation of the parametric bootstrap Mantel–Haenszel \(\text{MH} \chi ^2_{testlet}\) is augmented by simulation studies for assessing the performance of \(\text{MH} \chi ^2_{testlet}\) statistic under diverse conditions.