Extreme response style (ERS), the tendency of participants to endorse the extreme categories of an item partially independent of item content, has repeatedly been found to decrease the validity of Likert-type scale results. For this reason, many IRT models have been developed that attempt to detect and correct for ERS. Despite the substantive literature on ERS and modeling of ERS, several important questions remain. To date, there is no clear estimate of how often ERS occurs in practice across a variety of scales and populations. In addition, there is little guidance on what item parameters for ERS models are commonly found in empirical data, while this information is crucial to inform future methodological studies utilizing ERS models. Finally, there is only limited information available on which ERS models tend to fit the data best. The current study sets out to address these three issues by analyzing data from the Programme for International Student Assessment using a generalized partial credit model, several multidimensional nominal response models, and several IRTree models. Results indicate an extremely high prevalence of ERS across scales, populations, and timepoints. Item parameters for future methodological studies are presented, and a general preference for IRTree models over MNRM models is found in many datasets. Implications for futures studies are discussed, and recommendations for practice are made.
Schoenmakers et al. (Thu,) studied this question.