Riskier Tests of the Validity of the Bifactor Model of Psychopathology
By Ashley L. Watts, Holly E. Poore, I. Waldman. Clinical psychological science : a journal of the Association for Psychological Science, 2019
133 citations recorded by the source corpus.
We advanced several “riskier tests” of the validity of bifactor models of psychopathology, which included that the general and specific psychopathology factors should be reliable and well represented by their respective indicators and that including a general factor should improve on the correlated factor model’s external validity. We compared bifactor and correlated factors models of psychopathology using data from a community sample of youth (N = 2,498) whose parents provided ratings on psychopathology and theoretically relevant external criteria (i.e., personality, aggression, antisociality). Bifactor models tended to yield either general or specific factors that were unstable and difficult to interpret. The general factor appeared to reflect a differentially weighted amalgam of psychopathology rather than a liability for psychopathology broadly construed. With rare exceptions, bifactor models did not explain additional variance in first-order psychopathology symptom dimensions or external criteria compared with correlated factors models. Together, our findings call into question the validity of bifactor models of psychopathology and the p factor more broadly.
Subfields: Clinical Psychology
View Paper: https://www.semanticscholar.org/paper/81f026e17a77ae4242ee168583a3daf52acfc5f1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Clinical Psychology
Citations in the corpus
- Lack of Theory Building and Testing Impedes Progress in The Factor and Network Literature (2020, background): “The p factor literature provides an interesting example in this regard, where initiatives like the Hierarchical Taxonomy Of Psychopathology (HiTOP) are primarily concerned with describing data, but solely use one particular type of statistical model—the reflective latent variable model—that imposes ”