2018/01/11 by Sien Deng, Danielle E. McCarthy, Megan E. Piper +2 · 1 voice · 1 citation
Biochemistry, Genetics and Molecular Biology · Psychology · #Behavioral Health and Interventions #Genetic Mapping and Diversity in Plants and Animals #Mental Health Research Topics
paper · doi:10.1080/00273171.2017.1413636
openalex publication_date 2018/01/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/02
Extreme response style (ERS) has the potential to bias the measurement of intra-individual variability in psychological constructs. This paper explores such bias through a multilevel extension of a latent trait model for modeling response styles applied to repeated measures rating scale data. Modeling responses to multi-item scales of positive and negative affect collected from smokers at clinic visits following a smoking cessation attempt revealed considerable ERS bias in the intra-individual sum score variances. In addition, simulation studies suggest the magnitude and direction of bias due to ERS is heavily dependent on the mean affect level, supporting a model-based approach to the study and control of ERS effects. Application of the proposed model-based adjustment is found to improve intra-individual variability as a predictor of smoking cessation.