Abstract
Objective: Past taxometric studies of depression have yielded equivocal results. Diversity of sample type may provide one explanation for this. The aim of the present study was to examine the latent structure of depression across clinical and community samples using exactly the same taxometric procedures involving exactly the same indicators of depression.
Method: Two taxometric procedures, MAXEIG (maximum eigenvalue) and MAMBAC (mean above minus mean below a cut), were carried out on a clinical sample of 960 outpatients with mood and anxiety disorders. Simulated categorical and dimensional data sets as well as other consistency tests aided in the interpretation of the research data. Results were compared to a prior taxometric analysis in a community sample.
Results: The results of the current taxometric analyses were consistent with a dimensional latent structure and were compatible with the findings from identical analyses in a community sample.
Conclusions: The findings of the current study highlight the importance of identifying factors that may contribute to, and explain, differences in the identified latent structure of depression.