Citation

Bornovalova MA, Choate AM, Fatimah H, Petersen KJ, Wiernik BM. Biol. Psychiatry 2020; 88(1): 18-27.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.biopsych.2020.01.013

PMID

32199605

Abstract

Co-occurrence of psychiatric disorders is well documented. Recent quantitative efforts have moved toward an understanding of this phenomenon, with the general psychopathology or p-factor model emerging as the most prominent characterization. Over the past decade, bifactor model analysis has become increasingly popular as a statistical approach to describe common/shared and unique elements in psychopathology. However, recent work has highlighted potential problems with common approaches to evaluating and interpreting bifactor models. Here, we argue that bifactor models, when properly applied and interpreted, can be useful for answering some important questions in psychology and psychiatry research. We review problems with evaluating bifactor models based on global model fit statistics. We then describe more valid approaches to evaluating bifactor models and highlight 3 types of research questions for which bifactor models are well suited to answer. We also discuss the utility and limits of bifactor applications in genetic and neurobiological research. We close by comparing advantages and disadvantages of bifactor models with other analytic approaches and note that no statistical model is a panacea to rectify limitations of the research design used to gather data.

Language: en

Keywords

Bifactor; Construct validity; Criterion validity; General psychopathology factor; Humans; Mental Disorders; Models, Statistical; Neurobiology; Nomological net; Psychiatry; Psychopathology; Structural equations modeling; Taxonomy