Beth Ann Griffin

Beth Ann Griffin
Senior Statistician


Ph.D. in biostatistics, Harvard University; S.M. in biostatistics, Harvard University; B.A. in mathematics, University of Pennsylvania

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Beth Ann Griffin is a senior statistician at RAND and codirector the NIDA-funded RAND/USC Opioid Policy Tools and Information Center (OPTIC) whose goal is to foster innovative research, tools, and methods for tackling the opioid epidemic. Her statistical research has focused on methods for estimating causal effects using observational data. Her public health research has primarily fallen into three areas: (1) the effects of gun and opioid state policies on outcomes, (2) substance use treatment evaluations for adolescents, and (3) the impact of nongenetic factors on Huntington's disease.

Griffin codirected the RAND Center for Causal Inference between 2013 and 2018. She has served as the principal investigator on four grants sponsored by the National Institute of Drug Abuse (NIDA), the latest two devoted to developing new tools and methods to understand causal mediation and moderation and assess the sensitivity of effect estimates to omitted variables (, and well-operationalized, empirically-supported sequences of decision rules—known as “Adaptive Interventions” (AIs)—to provide guidance about substance-use services decisions for adolescent clients.

Griffin's research has appeared in leading journals such as Drug and Alcohol Dependence, Statistics in Medicine, Journal of the American Statistical Association, Annals of Applied Statistics, Journal of Causal Inference, and American Journal of Public Health. Griffin also serves on the editorial board of the Annals of Applied Statistics. She received her Ph.D. in biostatistics from Harvard University.

Selected Publications

Griffin, B.A., Schuler, M, Stone, E.M., Patrick, S.W., Stein, BD., Scherling, A., & Stuart, E., "Identifying optimal methods for addressing confounding bias when estimating the effects of state-level policies," Epidemiology, 34(6), 2023

Griffin, B.A., Schuler, M.S., Stuart, E.A., Patrick, S., McNeer, E., Smart, R., Powell, D., Stein, B.D., Schell, T.L., Pacula, R.L. , Moving beyond the classic difference-in-differences model: a simulation study comparing statistical methods for estimating effectiveness of state-level policies, BMC Medical Research Methodology., 2021

McCaffrey, DF, Griffin, BA, Almirall, D, Slaughter, ME, Ramchand, R, Burgette, LF, "A tutorial on propensity score estimation for multiple treatments using generalized boosted models," Statistics in Medicine, 32(19), 2013

Griffin, B. A., Booth, M. S., Busse, M., Wild, E. J., Setodji, C., Warner, J. H., Sampaio, C., Mohan, A. , Estimating the casual effects of modifiable, non-genetic factors on Huntington disease progression using propensity score weighting, Parkinsonism and Related Disorders 83: 56-62. , 2021

15.Schell, T.L., Cefalu, M., Griffin, B. A., Smart, R., & Morral, A.R. , Changes in firearm mortality following the implementation of state laws regulating firearm access and use., Proceedings of the National Academy of Sciences of the United States of America, 117(26), 14906-14910. , 2020

Griffin, BA, Ramchand, R, Almirall, D, Slaughter, ME, Burgette, LF, McCaffrey, D, "Estimating the causal effects of cumulative treatment episodes for adolescents using marginal structural models and inverse probability of treatment weighting," Drug and Alcohol Dependence, 136(1), 2014

Sanchez, R., Griffin, B.A., McCafferty, D.M., Best Practices in Statistical Computing, Statistics in Medicine, 2021

Griffin, BA., Schuler, MS, Cefalu, M, Ayer, L, Godley, M, Greifer, N, Coffman, D, McCaffrey, D, "Propensity Score Weighting for Moderation Analysis With Categorical Variables: An Application Examining Smoking Disparities Among Sexual Minority Adults," Medical Care: Statistical Workshop Series, 61(12), 2023