What is it about?
Building on previous simulation studies, we found that fit statistics have a predetermined preference for the confirmatory bifactor model over nested alternatives (correlated factor and higher-order models) when they are fit to data containing unmodeled complexities of adequate size.
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Why is it important?
The mathematical correctness of global fit indices does not preclude the tendency for researchers to be misled and, in turn, prone to make problematic inferences about the bifactor model’s scientific value.
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This page is a summary of: Are fit indices used to test psychopathology structure biased? A simulation study., Journal of Abnormal Psychology, July 2019, American Psychological Association (APA),
DOI: 10.1037/abn0000434.
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