Tianxi Cai
Affiliations: | Biostatistics | Harvard University, Cambridge, MA, United States |
Area:
Biostatistics Biology, EpidemiologyGoogle:
"Tianxi Cai"Children
Sign in to add trainee| Larry F. Leon | grad student | 2005 | Harvard |
| Samuel A. McDaniel | grad student | 2007 | Harvard |
| Jessica N. Minnier | grad student | 2012 | Harvard |
| Layla M. Parast | grad student | 2012 | Harvard |
| Jennifer A. Sinnott | grad student | 2012 | Harvard |
| Denis M. Agniel | grad student | 2014 | Harvard |
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Publications
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| Parast L, Cai T, Tian L. (2024) A rank-based approach to evaluate a surrogate marker in a small sample setting. Biometrics. 80 |
| Parast L, Tian L, Cai T, et al. (2023) Statistical Methods to Evaluate Surrogate Markers. Medical Care |
| Zheng Y, Lu T, Cai T. (2023) EFFICIENT AND ROBUST ESTIMATION OF -YEAR RISK PREDICTION MODELS LEVERAGING TIME VARYING INTERMEDIATE OUTCOMES. Statistica Sinica. 31: 1531-1547 |
| Parast L, Tian L, Cai T, et al. (2023) Can earlier biomarker measurements explain a treatment effect on diabetes incidence? A robust comparison of five surrogate markers. Bmj Open Diabetes Research & Care. 11 |
| Parast L, Cai T, Tian L. (2022) Using a surrogate with heterogeneous utility to test for a treatment effect. Statistics in Medicine |
| Gronsbell J, Liu M, Tian L, et al. (2022) Efficient Evaluation of Prediction Rules in Semi-Supervised Settings under Stratified Sampling. Journal of the Royal Statistical Society. Series B, Statistical Methodology. 84: 1353-1391 |
| Han L, Wang X, Cai T. (2022) Identifying surrogate markers in real-world comparative effectiveness research. Statistics in Medicine |
| Wang X, Parast L, Han L, et al. (2022) Robust approach to combining multiple markers to improve surrogacy. Biometrics |
| Parast L, Cai T, Tian L. (2021) Testing for heterogeneity in the utility of a surrogate marker. Biometrics |
| Hou J, Chan SF, Wang X, et al. (2021) Risk prediction with imperfect survival outcome information from electronic health records. Biometrics |