Evaluation on types of invariance in studying extreme response bias with an IRTree approach

In recent years, item response tree (IRTree) approaches have received increasing attention in the response style literature for their ability to partial out response style latent variables as well as associated item parameters. When an IRTree approach is adopted to measure extreme response styles, directional and content invariance could be assumed at the latent variable and item parameter levels. In this study, we propose to evaluate the empirical validity of these invariance assumptions by employing a general IRTree model with relaxed invariance assumptions. This would allow us to examine extreme response biases, beyond extreme response styles. With three empirical applications of the proposed evaluation, we find that relaxing some of the invariance assumptions improves the model fit, which suggests that not all assumed invariances are empirically supported. Specifically, at the latent variable level, we find reasonable evidence for directional invariance but mixed evidence for content invariance, although we also find that estimated correlations between content-specific extreme response latent variables are high, hinting at the potential presence of a general extreme response tendency. At the item parameter level, we find no directional or content invariance for thresholds and no content invariance for slopes. We discuss how the variant item parameter estimates obtained from a general IRTree model can offer useful insight to help us understand response bias related to extreme responding measured within the IRTree framework.