Eric B. Laber, Ph.D.
Affiliations: | 2011 | University of Michigan, Ann Arbor, Ann Arbor, MI |
Area:
StatisticsGoogle:
"Eric Laber"Parents
Sign in to add mentor| Susan A. Murphy | grad student | 2011 | University of Michigan | |
| (Adaptive confidence intervals for non-smooth functionals.) | ||||
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Publications
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| Manschot C, Laber E, Davidian M. (2023) Interim monitoring of sequential multiple assignment randomized trials using partial information. Biometrics |
| Luckett DJ, Laber EB, Kim S, et al. (2021) Estimation and Optimization of Composite Outcomes. Journal of Machine Learning Research : Jmlr. 22 |
| Rashid NU, Luckett DJ, Chen J, et al. (2021) High-Dimensional Precision Medicine From Patient-Derived Xenografts. Journal of the American Statistical Association. 116: 1140-1154 |
| Guan Q, Reich BJ, Laber EB, et al. (2020) Bayesian Nonparametric Policy Search with Application to Periodontal Recall Intervals. Journal of the American Statistical Association. 115: 1066-1078 |
| Luckett DJ, Laber EB, Kahkoska AR, et al. (2020) Estimating Dynamic Treatment Regimes in Mobile Health Using V-learning. Journal of the American Statistical Association. 115: 692-706 |
| Luckett DJ, Laber EB, El-Kamary SS, et al. (2020) Receiver operating characteristic curves and confidence bands for support vector machines. Biometrics |
| Dong L, Laber E, Goldberg Y, et al. (2020) Ascertaining properties of weighting in the estimation of optimal treatment regimes under monotone missingness. Statistics in Medicine |
| Hu W, Laber EB, Barker C, et al. (2019) Assessing Tuning Parameter Selection Variability in Penalized Regression. Technometrics : a Journal of Statistics For the Physical, Chemical, and Engineering Sciences. 61: 154-164 |
| Zhao YQ, Laber EB, Ning Y, et al. (2019) Efficient augmentation and relaxation learning for individualized treatment rules using observational data. Journal of Machine Learning Research : Jmlr. 20 |
| Zhang Y, Laber EB, Davidian M, et al. (2018) Interpretable Dynamic Treatment Regimes. Journal of the American Statistical Association. 113: 1541-1549 |