Dr. Sarah Depaoli is Professor of Quantitative Methods, Measurement & Statistics at the University of California, Merced. She received her Ph.D. in 2010 in Quantitative Methods (minor: Mathematical Statistics) from University of Wisconsin, Madison. She is an elected member since 2016 of the Society of Multivariate Experimental Psychology (capped at 65 active members world-wide).
Dr. Depaoli teaches undergraduate statistics and a variety of graduate courses in quantitative methods. 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.
Finally, Dr. Depaoli has served the field in a variety of ways, including as Associate Editor for: Multivariate Behavioral Research (2017-present), Psychological Methods (2018-present), and Journal of the Royal Statistical Society--Series A (2022-present).
