Browsing by Author "Wright, Aidan G. C."

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    The Latent Structure of Interpersonal Problems: Validity of Dimensional, Categorical, and Hybrid Models
    Wendt, Leon P.; Wright, Aidan G. C.; Pilkonis, Paul A.; Nolte, Tobias; Fonagy, Peter; Montague, P. Read; Benecke, Cord; Krieger, Tobias; Zimmermann, Johannes (American Psychological Association, 2019-11-01)
    Interpersonal problems are key transdiagnostic constructs in psychopathology. In the past, investigators have neglected the importance of operationalizing interpersonal problems according to their latent structure by using divergent representations of the construct: (a) computing scores for severity, agency, and communion ("dimensional approach"), (b) classifying persons into subgroups with respect to their interpersonal profile ("categorical approach"). This hinders cumulative research on interpersonal problems, because findings cannot be integrated both from a conceptual and a statistical point of view. We provide a comprehensive evaluation of interpersonal problems by enlisting several large samples (Ns = 5,400, 491, 656, and 712) to estimate a set of latent variable candidate models, covering the spectrum of purely dimensional (i.e., confirmatory factor analysis using Gaussian and nonnormal latent t-distributions), hybrid (i.e., semiparametric factor analysis), and purely categorical approaches (latent class analysis). Statistical models were compared with regard to their structural validity, as evaluated by model fit (corrected Akaike's information criterion and the Bayesian information criterion), and their concurrent validity, as defined by the models' ability to predict relevant external variables. Across samples, the fully dimensional model performed best in terms of model fit, prediction, robustness, and parsimony. We found scant evidence that categorical and hybrid models provide incremental value for understanding interpersonal problems. Our results indicate that the latent structure of interpersonal problems is best represented by continuous dimensions, especially when one allows for nonnormal latent distributions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).