In educational testing, differential item functioning (DIF) examines whether item parameters differ across examinee characteristics. In this study, DIF is viewed not as bias but as item parameter heterogeneity reflecting differential engagement with related subskills. Using recursive partitioning based on parametric logistic item response theory (PL IRTree) models, this study investigated item functioning heterogeneity in a high-stakes reading comprehension test regarding vocabulary, grammar, and gender based on responses of 14,936 examinees. The comparison of Rasch tree, 2PL, 3PL, and 4PL IRTrees showed that the Rasch tree could better capture the structure of the data. The Educational Testing Service (ETS) classification scheme using the Mantel-Haenszel log odds ratio was then used to quantify effect sizes. The Rasch tree yielded 11 nodes, indicating subgroup differences in item difficulty, with seven items showing moderate parameter variation across five nodes. Except for one vocabulary-focused item showing systematic sensitivity to vocabulary knowledge, item parameter variation associated with lexico-grammatical knowledge was small, suggesting limited heterogeneity attributable to these subskills. Gender-related differences in item functioning appeared only within a subgroup of examinees with relatively high grammar-vocabulary scores. PL IRTree models can reveal item-level heterogeneity and the role of correlated subskills in shaping reading comprehension item functioning.
