- Steingrimsson, J.A.*, Diao, L.*, & Strawderman, R. L. Censoring Unbiased Regression Trees and Ensembles. Journal of the American Statistical Association. (In Press). [Supplementary Material]
- Hu, C., & Steingrimsson, J.A.,. Personalized Risk Prediction in Clinical Oncology Research: Applications and Practical Issues Using Survival Trees and Random Forests. Journal of Biopharmaceutical Statistics. (In Press).
- Steingrimsson, J.A., & Strawderman, R.L. (2017). Estimation in the semiparametric accelerated failure time model with missing covariates: improving efficiency through augmentation. Journal of the American Statistical Association. Volume 519. 1221-1235. [Supplementary Material]
- Steingrimsson, J.A., Hanley, D.F, & Rosenblum, M. (2017). Improving precision by adjusting for baseline variables in randomized trials with binary outcomes, without regression model assumptions. Contemporary Clinical Trials. Volume 54. 18-24. [Code included in web appendix].
- Steingrimsson, J.A., Diao, L., Molinaro, A.M., & Strawderman, R. L. (2016). Doubly Robust survival trees. Statistics in Medicine. Volume 35. Issue 20. 3595 – 3612. [Supplementary Material]
- Vangay, P., Steingrimsson, J.A., Wiedmann, M., & Stasiewicz, M.J. (2014). Classification of Listeria monocytogenes persistence in retail delicatessen environments using expert elicitation and machine learning. Risk Analysis. Volume 34. Issue 10. 1830 – 1845.
- Rosenblum, M, & Steingrimsson, J.A. Matching the Efficiency Gains of the Logistic Regression Estimator while Avoiding its Interpretability Problems, in Randomized Trials.
- Steingrimsson, J. A., Betz, J., Qian, T., and Rosenblum, M. Optimized Adaptive Enrichment Designs for Multi-ArmTrials: Learning which Subpopulations Benefit from Different Treatments.
- Betz, J., Steingrimsson, J. A., Qian, T., and Rosenblum, M. Comparison of Adaptive Randomized Trial Designs for Time-to-Event Outcomes that Expand Versus Restrict Enrollment Criteria, to Test Non-Inferiority.
- Steingrimsson, J. A. & Yang, J. Subgroup Identification using Covariate Adjusted Interaction Trees.
*Indicates joint first authorship