Modeling Response Style Using Vignettes and Person-Specific Item Response Theory

Abstract

Responses to survey data are determined not only by item characteristics and respondents’ trait standings but also by response styles. Recently, methods for modeling response style with personality and attitudinal data have turned toward the use of anchoring vignettes, which provide fixed rating targets. Although existing research is promising, a few outstanding questions remain. First, it is not known how many vignettes and vignette ratings are necessary to identify response style parameters. Second, the comparative accuracy of these models is largely unexplored. Third, it remains unclear whether correcting for response style improves criterion validity. Both simulated data and data observed from a population-representative sample responding to a measure of personality pathology (the Personality Inventory for DSM-5 [PID-5]) were modeled using an array of response style models. In simulations, most models estimating response styles outperformed the graded response model (GRM), and in observed data, all response style models were superior to the GRM. Correcting for response style had a small, but in some cases significant, effect on the prediction of self-reported social dysfunction.