Abstract

Item response tree model (IRTree) is a sort of a multidimensional item response theory that incorporates a tree structure depicting a respondent's cognitive response process into item response theory. IRTree has recently received considerable attention from researchers for measuring extreme response style (ERS) that can threaten reliability and factor structure in self-report survey data. In addition to the work of IRTree, we extend IRTree as the mixture item response tree model (MixIRTree), which combines latent class analysis with IRTree for measuring and investigating the possible heterogeneity of data caused by ERS. For analyses, this study used the body symptom and depression scales of the emotional problems in the third wave of KCYPS 2018. The results of the study are as follows. First, the three latent classes were captured, showing the different levels of ERS. The latent class 3 did not show the ERS tendency than the latent classes 1 and 2. The latent class 1 showed the largest ERS tendency. Second, the ERS tendency across the latent classes was different between the negative affect scales. For example, the ERS tendency of the latent class 1 was larger in the depression scale than body symptom scale, while the ERS tendency of the latent class 2 was larger in the body symptom scale than the depression scale. Based on these findings, we provide practical implications of the MixIRTree for measuring the heterogeneity of ERS and discuss the future direction for further study.