August Morgan is an associate statistician at RAND. Morgan's research expertise is in causal inference and Bayesian statistical methods for social sciences applications. Morgan's methodological interests are broad and include nonparametric and machine learning methods (including Bayesian Additive Regression Tree, or BART, models), multilevel modeling, methods for survey data, and methods for studying treatment effect heterogeneity. Morgan's applied work has studied adolescent mental health, educational interventions, voter mobilization, and air force recruiting.
Morgan earned a bachelor's degree in mathematics from Louisiana State University and a Ph.D. in statistics from the University of Texas at Austin.
Bachelor of Science in mathematics, Louisiana State University and Agricultural & Mechanical College; Doctor of Philosophy in statistics, The University of Texas at Austin
