I am an Associate Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. My research interests include adaptive clinical trial designs, robustness to model misspecification, causal inference, and HIV/AIDS prevention and treatment.
I am honored to be one of five recipients of the 2017 Burroughs Wellcome Fund (BWF) Innovation in Regulatory Science Awards: “BWF’s Innovation in Regulatory Science Awards provide up to $500,000 over five years to academic investigators developing new methodologies or innovative approaches in regulatory science that will ultimately inform the regulatory decisions the Food and Drug Administration (FDA) and others make.”
Selected Publications (Click here for CV).
* Indicates primary mentorship of trainee on this manuscript
- Rosenblum, M., Miller, P., Reist, B., Stuart, E., Thieme, M., and Louis, T. (2019) Adaptive Design in Surveys and Clinical Trials: Similarities, Differences, and Opportunities for Cross-Fertilization. Journal of the Royal Statistical Society, Series A (Statistics in Society). 182, 963-982. https://doi.org/10.1111/rssa.12438 Article selected for presentation at 2019 Royal Statistical Society International Conference.
- Hanley, D. F., Thompson, R. E., Rosenblum, M., Yenokyan, G., Lane K., McBee, N., Mayo S. W., Bistran-Hall, A. J., Gandhi, D. Mould, W. A., Ullman, N., Ali, H., Carhuapoma, J. R. Kase, C. S., Lees, K. R., Dawson, J., Wilson, A., Betz, J. F., Sugar, E., Hao, Y., Avadhani, R., Caron, J.-L., Harrigan, M. R., Carlson, A. P., Bulters, D., LeDoux, D. E., Huang, J., Cobb, C., Gupta, G., Kitagawa, R., Chicoine, M. R., Patel, H., Dodd, R., Camarata, P. J., Wolfe, S., Stadnik, A., Money, P. L., Mitchell, P., Sarabia, R., Harnof, S., Barzo, P., Unterberg, A., Teitelbaum, J. S., Wang, W., Anderson, C. S., Mendelow, A. D., Gregson, B., Janis, S., Vespa, P., Ziai, W., Zuccarello, M., Awad, I. A., for the MISTIE III Investigators. (2019) Efficacy and safety of minimally invasive surgery with thrombolysis in intracerebral haemorrhage evacuation (MISTIE III): a randomised, controlled, open-label, blinded endpoint phase 3 trial. The Lancet. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(19)30195-3
- *Wang, B., Ogburn, E., and Rosenblum, M. (2019) Analysis of Covariance (ANCOVA) in Randomized Trials: More Precision and Valid Confidence Intervals, Without Model Assumptions. Biometrics. https://doi.org/10.1111/biom.13062
- Wu, A.W., Weston, C.M., Chidinma, A.I., Ruberman, C., Bone, L., Boonyasai, R., Hwang, S., Gentry, J., Purnell, L., Lu, Yanyan, Liang, S., and Rosenblum, M. The Baltimore CONNECT (Community-based Organizations Neighborhood Network: Enhancing Capacity Together) Cluster Randomized Controlled Trial. (2019) American Journal of Preventive Medicine. https://doi.org/10.1016/j.amepre.2019.03.013
- *Huang, E. J., Fang, E. X., Hanley, D. F., and Rosenblum, M. (In Press) Constructing a Confidence Interval for the Fraction Who Benefit from Treatment, Using Randomized Trial Data. https://doi.org/10.1111/biom.13101
- Steingrimsson, J.A., Betz, J., Qian, T., and Rosenblum, M. (In Press) Optimized Adaptive Enrichment Designs for Three-Arm Trials: Learning which Subpopulations Benefit from Different Treatments. https://doi.org/10.1093/biostatistics/kxz030
- *Fisher, A., Rosenblum, M. & for the Alzheimer’s Disease Neuroimaging Initiative (2018) Stochastic Optimization of Adaptive Enrichment Designs for Two Subpopulations, Journal of Biopharmaceutical Statistics, 28(5), 966-982, Open Access link to Journal Version
- Dıaz, I., Colantuoni, E., Hanley, D. F., and Rosenblum, M. (2018) Improved Precision in the Analysis of Randomized Trials with Survival Outcomes, without Assuming Proportional Hazards. Lifetime Data Analysis. PDF
- Rosenblum, M., and Hanley, D.F. (2017) Topical Review: Adaptive Enrichment Designs for Stroke Clinical Trials. Stroke. 48(6). LINK TO PAPER
- Steingrimsson, J. A., Hanley, D. F., and Rosenblum, M., (2017) Improving Precision by Adjusting For Baseline Variables in Randomized Trials with Binary Outcomes, without Regression Model Assumptions. Contemporary Clinical Trials.
- *Huang, E., Fang, E., Hanley, D., and Rosenblum, M., (2017) Inequality In Treatment Benefits: Can We Determine If a New Treatment Benefits the Many or the Few? Biostatistics. PDF Version
- Rosenblum, M., Fang, X., and Liu, H. Optimal, Two Stage, Adaptive Enrichment Designs for Randomized Trials Using Sparse Linear Programming. (Under Review): LINK TO WORKING PAPER
- Rosenblum, M., Qian, T., Du, Y., and Qiu, H., Fisher, A. (2016) Multiple Testing Procedures for Adaptive Enrichment Designs: Combining Group Sequential and Reallocation Approaches. Biostatistics. 17(4), 650-662. PDF version
- Rosenblum, M., Thompson, R., Luber, B., Hanley, D. (2016) Group Sequential Designs with Prospectively Planned Rules for Subpopulation Enrichment. Statistics in Medicine. 35(21), 3776-3791. http://goo.gl/7nHAVn
- Patil, P., Colantuoni, E., Leek, J. T., Rosenblum, M. (2016) Measuring the Contribution of Genomic Predictors to Improving Estimator Precision in Randomized trials. Contemporary Clinical Trials Communications. 48-54. http://dx.doi.org/10.1016/j.conctc.2016.03.001
- Diaz, I., Colantuoni, E., Rosenblum, M. (2016) Enhanced Precision in the Analysis of Randomized Trials with Ordinal Outcomes. Biometrics. (72) 422-431 [LINK]
- Rosenblum, M. (2015) Adaptive Randomized Trial Designs that Cannot Be Dominated By Any Standard Design at the Same Total Sample Size. 102(1). 191-202. Biometrika. [LINK]
- Rosenblum, M, Liu H, Yen E-H. (2014) “Optimal Tests of Treatment Effects for the Overall Population and Two Subpopulations in Randomized Trials, Using Sparse Linear Programming” Journal of the American Statistical Association (Theory and Methods). Volume 109. Issue 507. 1216-1228. [LINK]
Example of Optimal Rejection Regions Produced by Method in Above Paper:
- Rosenblum, M, (2014) “Uniformly Most Powerful Tests for Simultaneously Detecting a Treatment Effect in the Overall Population and at Least One Subpopulation” Journal of Statistical Planning and Inference. Volume 155. 107-116. [LINK]
Papers on Improved Design and Analysis for Randomized Trials
- Rosenblum, M., Fang, X., and Liu, H., (2014) Optimal, Two Stage, Adaptive Enrichment Designs for Randomized Trials Using Sparse Linear Programming. [Click here for Working Paper] [Click here for slides from recent talk]
- Colantuoni, E. and Rosenblum, M. (2015) Leveraging Prognostic Baseline Variables to Gain Precision in Randomized Trials. Statistics in Medicine. doi: 10.1002/sim.6507 [LINK to Paper] [Related Talk with Overview of Covariate Adjustment]
- Huang, E. Fang, E., Hanley, D., and Rosenblum, M. (2015) Inequality In Treatment Benefits: Can We Determine If a New Treatment Benefits The Many Or The Few? Johns Hopkins University, Dept. of Biostatistics Working Papers. [Working Paper]
- Rosenblum, M., Qian, T., Du, Y., Qiu, H. (2015) Adaptive Enrichment Designs For Randomized Trials With Delayed Endpoints, Using Locally Efficient Estimators To Improve Precision. Johns Hopkins University, Dept. of Biostatistics Working Papers. [Working Paper]
- Papers from half-day Workshop led by Michael Rosenblum on Adaptive Designs at the FDA, from the PACES (Partnership in Applied Comparative Effectiveness Science) Collaboration, June 26, 2013. [LINK]
Causal Inference Working Group, Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
mrosen “–at–” jhu–dot–(dashes and this phrase inserted to avoid spam) edu