Sarah Depaoli

Sarah Depaoli is a Professor of Quantitative Methods, Measurement, and Statistics, and Department Chair of Psychological Sciences at the University of California, Merced. She holds a Ph.D. in Quantitative Methods from the University of Wisconsin, Madison (2010). Her research focuses on Bayesian statistics, structural equation modeling (SEM), and mixture models, with a particular emphasis on improving model robustness and addressing methodological challenges in latent variable analysis.

Dr. Depaoli’s work includes advancing Bayesian approaches for SEM, latent growth curve models, and finite mixture models. She has authored the book *Bayesian Structural Equation Modeling* (Guilford Press, 2021), which serves as a key resource for researchers and students. She currently serves as an Associate Editor for *Multivariate Behavioral Research*, *Psychological Methods*, and the *Journal of the Royal Statistical Society, Series A*.

Her research interests span prior specification in Bayesian models, class enumeration in mixture models, and the application of non-parametric methods. She teaches undergraduate statistics and graduate courses in quantitative methods at UC Merced. Her contributions to statistical methodology have been recognized through editorial roles and her influential publications on Bayesian techniques.