Jason A. Roy, PhD
| Office Location | 618, Blockley Hall |
| Office Phone | 215-746-4225 |
| jaroy@mail.med.upenn.edu | |
Faculty Information | |
| CCEB Appointment | Senior Scholar, Biostatistics |
| Primary Faculty Appointment | Assistant Professor of Biostatistics @ HUP, University of Pennsylvania Perelman SOM |
Research Statement
Dr Roy's current methodological research interests are motivated by challenges in carrying out comparative effectiveness research studies using large administrative databases. In particular, he is focusing on missing data issues, estimating causal comparisons from many possible treatments, dynamic treatment strategies, causal mediation models and prediction modeling of structured and unstructured data using data mining and machine learning. He is also an investigator on several comparative effectiveness research projects in pharmacoepidemiology.
Selected Publications
Roy, J, Lin, X. and Ryan, L.: Scaled marginal model for multiple continuous outcomes. Biostatistics 4: 371-383, 2003
Roy, J. Modelling longitudinal data with nonignorable dropouts using a latent dropout class model. Biometrics. 59: 829-836, 2003.
Hogan, J.W., Roy, J. and Korkontzelou, C.: Handling dropout in longitudinal studies. Statistics in Medicine 23: 1455-1497, 2004.
Roy, J. Alderson, D., Hogan, J.W. and Tashima, K.T.: Conditional inference methods for incomplete Poisson data with endogenous time-varying covariates: emergency department use among HIV-infected women. Journal of the American Statistical Association 101: 424-434, 2006.
Roy, J. and Daniels, M.: A general class of pattern mixture models for nonignorable dropout with many possible dropout times. Biometrics 64: 538-545, 2008.
Roy, J., Hogan, J.W. and Marcus, B.H.: Principal stratification with predictors of compliance for randomized trials with two active treatments. Biostatistics 9: 277-289, 2008.
Roy, J. and Stewart, W.F. Estimation of age-specific incidence rates from cross-sectional survey data. Statistics in Medicine 28: 588-596, 2010.
Wu, J., Roy, J., Steward WF. Prediction modeling using EHR data: challenges, strategies, and a comparison of machine learning approaches. Medical Care, 48(6 Suppl): S106-113, 2010.
Roy, J. and Stewart, W. F. Methods for estimating remission rates from cross-sectional survey data: application and validation using data from a national migraine study. American Journal of Epidemiology, 173(8):949-55, 2011.
