A Mixture IRT Model for Handling Different Types of Careless Respondents

Careless and insufficient effort responding (C/IER) in self-report questionnaires occurs when responses are given without attention being paid to the item content. In this study, we provide a mixture item response theory (IRT) model that efficiently accommodates various C/IER types and can be easily implemented in standard IRT software. In an extensive simulation study, we evaluated the conditions that might facilitate the separation of respondents who exhibit and respondents who do not exhibit C/IER. The results indicate that, for all investigated patterns of C/IER, the suggested model performs well when scales comprise 10 or more items, include items that clearly differ from each other in their category thresholds (high item heterogeneity), and combine positively and negatively worded items. Empirical support for interpreting the latent class variable as assessing C/IER was obtained by reanalyzing a publicly available Big Five inventory data set. The model-based identification of C/IER was closely aligned with results from attention check items; the mixture IRT model was more sensitive to differences in the prevalence of C/IER across assessment platforms than the attention check items were.