The Challenges of Fitting an Item Response Theory Model to the Social Anhedonia Scale

Abstract

This study explored the application of latent variable measurement models to the Social Anhedonia Scale (SAS; Eckblad, Chapman, Chapman, & Mishlove, 1982), a widely used and influential measure in schizophrenia-related research. Specifically, we applied unidimensional and bifactor item response theory (IRT) models to data from a community sample of young adults (n = 2,227). Ordinal factor analyses revealed that identifying a coherent latent structure in the 40-item SAS data was challenging due to (a) the presence of multiple small content clusters (e.g., doublets); (b) modest relations between those clusters, which, in turn, implies a general factor of only modest strength; (c) items that shared little variance with the majority of items; and (d) cross-loadings in bifactor solutions. Consequently, we conclude that SAS responses cannot be modeled accurately by either unidimensional or bifactor IRT models. Although the application of a bifactor model to a reduced 17-item set met with better success, significant psychometric and substantive problems remained. Results highlight the challenges of applying latent variable models to scales that were not originally designed to fit these models.