Jason Roy, PhD

Jason Roy is a Professor of Biostatistics and Chair of the Department of Biostatistics and Epidemiology. He is director of Rutgers University Biostatics and Epidemiology Services (RUBIES) and co-director of Biostatistics, Epidemiology, and Research Design (BERD) core, NJ ACTS. Previously, he was Professor of Biostatistics in the Department of Biostatistics, Epidemiology, and Informatics at the University of Pennsylvania.

1. Oganisian, A., Mitra, N., Roy, J. (2020) “A Bayesian nonparametric model for zero-inflated outcomes: Prediction, clustering, and causal estimation.”, Biometrics Vol. http://www.ncbi.nlm.nih.gov/pubmed/?term=32125699&report=abstract
2. Tan, Y., Roy, J. (2019) “Bayesian additive regression trees and the General BART model”, Statistics in Medicine. Vol. 38 http://www.ncbi.nlm.nih.gov/pubmed/?term=31460678&report=abstract
3. Zeldow, B., Roy, J. (2019) “A semiparametric modeling approach using Bayesian Additive Regression Trees with an application to evaluate heterogeneous treatment effects”, Annals of Applied Statistics Vol. 13 https://projecteuclid.org/euclid.aoas/1571277780
4. Roy, J., Lum, K., Zeldow, B., Dworkin, J., Re, V., Daniels, M. (2018) “Bayesian nonparametric generative models for causal inference with missing at random covariates.”, Biometrics Vol. 74 http://www.ncbi.nlm.nih.gov/pubmed/?term=29579341&report=abstract
5. Roy, J., Lum, K., Daniels, M. (2017) “A Bayesian nonparametric approach to marginal structural models for point treatments and a continuous or survival outcome.”, Biostatistics Vol. 18 http://www.ncbi.nlm.nih.gov/pubmed/?term=27345532&report=abstract
6. Kim, C., Daniels, M., Marcus, B., Roy, J. (2017) “A framework for Bayesian nonparametric inference for causal effects of mediation.”, Biometrics Vol. 73 http://www.ncbi.nlm.nih.gov/pubmed/?term=27479682&report=abstract