Speaker: Mijke Rhemtulla (Psychology, UC Davis)
Title: "Consequences of Mistaking the Measurement Model in SEM, Alternatives to Common Factors, and a Method for Model Selection"
Abstract: Much of the appeal of structural equation models lies in their capacity to account for measurement error by modeling abstract constructs (extraversion, quality of life, school readiness) as latent common factors. This features of SEMs has led researchers across the social sciences to use latent variable SEMs with little awareness of the assumptions that the reflective measurement model requires. But the choice of measurement model carries implications about the structure of data and about data-construct associations: An incorrect model can change the meaning of the construct and render structural relations uninterpretable. When a common factor model is mis-applied, structural model coefficients can be (highly) biased, and this bias can arise even when model fit is perfect. Recent developments allow for two alternative measurement models to be implemented in SEM: a composite score model with user-defined weights, and a composite score model with model-estimated weights. In this talk I discuss the problem and present the alternative measurement models, and I propose a statistical test that may help to identify the most appropriate measurement model given data.
Seminar Date/Time: Thursday June 1, 2023 at 4:10pm
Location: MSB 1147 (Colloquium Room)
Refreshments at 3:30pm, MSB 1147 Courtyard