Sarah Depaoli, PhD
INSTRUCTOR
Dr. Sarah Depaoli is Professor and Area Head of Quantitative Methods, Measurement, and Statistics at the University of California, Merced. Her research interests include examining different facets of Bayesian estimation for latent variable, growth, and finite mixture models. She has a continued interest in the influence of prior distributions and robustness of results under different prior specifications, as well as issues tied to latent class separation. Her recent research has focused on using Bayesian semi- and non-parametric methods for obtaining proper class enumeration and assignment, examining parameterization issues within Bayesian SEM, and studying the impact of priors on longitudinal models. She is the author of the book Bayesian Structural Equation Modeling, available through Guilford Press.
Learn more about Dr. Depaoli’s teaching and research here.
Workshops by Sarah Depaoli
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