A Bifactor Model of the Autism Spectrum Disorder Phenotype
Williams, Z. J. (2019). A Bifactor Model of the Autism Spectrum Disorder Phenotype. Journal of the American Academy of Child & Adolescent Psychiatry, 58(10), 1019-1021. https://doi.org/10.1016/j.jaac.2019.02.021
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Abstract
I read with interest the newly published work by Kim et al. describing the covariance structure of parent-reported autism spectrum disorder (ASD) symptoms.1 The authors compared many different latent class, factor analytic, and factor mixture models in a large, clinically referred sample, concluding that the ASD phenotype is best described by three continuous latent factors of social interaction, communication, and repetitive behavior. I found the study to be methodologically rigorous, employing robust estimation techniques, testing a wide range of categorical-dimensional hybrid models, and even replicating the rank-order of model choices in a separate sample. However, given the large reported interfactor correlations in the final model (r = 0.78-0.83; Kim et al., Figure 2), I was disappointed that the authors did not explore a bifactor model2 of ASD phenotypic traits. In this correspondance, I aim to demonstrate the ways in which bifactor models provide further insight into the structures of complex psychopathological constructs.
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Hyunsik Kim , Cara Keifer , Craig Rodriguez-Seijas , Nicholas Eaton , Matthew D Lerner , Kenneth Gadow (2019). Quantifying the Optimal Structure of the Autism Phenotype: A Comprehensive Comparison of Dimensional, Categorical, and Hybrid Models . Journal of the American Academy of Child & Adolescent Psychiatry, 58(9), 876-886.e2. Elsevier BV.Crossref OpenAlex OpenCitations
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Maxwell Mansolf , Steven P. Reise (2016). Exploratory Bifactor Analysis: The Schmid-Leiman Orthogonalization and Jennrich-Bentler Analytic Rotations . Multivariate Behavioral Research, 51(5), 698-717. Informa UK Limited.Crossref OpenAlex OpenCitations