PACES Adaptive Designs Workshop Papers


1. Rosenblum, M., Liu, H., and Yen, E-H. 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). In Press.

2. Rosenblum, M., Uniformly Most Powerful Tests for Simultaneously Detecting a Treatment Effect in the Overall Population and at Least One Subpopulation

3. Rosenblum, M., Luber, B., Thompson, R. Hanley, D. Adaptive Group Sequential Designs that Balance the Benefits and Risks of Expanding Inclusion Criteria

4. Rosenblum, M. and van der Laan, M. (2011) Optimizing randomized trial designs to distinguish which subpopulations benefit from treatment. Biometrika 98(4).

5. Rosenblum, M. (2013) Confidence Intervals for the Selected Population in Randomized Trials that Adapt the Population Enrolled, Biometrical Journal. 55(3), 322-340.

6. Luber, B., Rosenblum, M., and Chambaz, A. Trial Designs that Simultaneously Optimize the Population Enrolled and the Treatment Allocation Probabilities