Predictive Analytics

• Efficient Identification of Predictive Markers

• Risk Prediction under Efficient Two-phase Study Designs

• Machine Learning Approaches to Risk Prediction

• Quantifying Prediction Performance

Research Team

Cai, Tianxi

John Rock Professor of Population and Data Science, Professor of Biostatistics
Harvard T.H. Chan School of Public Health
Professor of Biomedical Informatics
Harvard Medical School

Neykov, Matey

Assistant Professor of Statistics
Carnegie Mellon University

Parast, Layla

Statistician
Rand Corporation

Tian, Lu

Professor of Biomedical Data Science
Stanford University

Uno, Hajime

Assistant Professor
Medicine, Harvard Medical School
Assistant Professor
Biostatistics and Computational Biology
Dana-Farber Cancer Institute

Wei, Lee Jen

Professor of Biostatistics
Harvard T.H. Chan School of Public Health

Selected Publications

• MO Goodman, L Chibnik, T Cai. “Variance components genetic association test for zero-inflated count outcomes”. Genetic Epidemiology 2018;43(1):82–101.
• J Gronsbell, J Minnier, S Yu, K Liao, T Cai. “Automated feature selection of predictors in electronic medical records data”. Biometrics 2019;75(1):268–277.
• C Hong, KP Liao, T Cai. “Semi-supervised validation of multiple surrogate outcomes with application to electronic medical records phenotyping”. Biometrics 2019;75(1):78–89.
• JL Gronsbell, T Cai. “Semi-supervised approaches to efficient evaluation of model prediction performance”. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2017;80(3):579–594.
• JA Sinnott, T Cai. “Pathway aggregation for survival prediction via multiple kernel learning”. Statistics in Medicine 2018;37(16):2501–2515.
• QM Zhou, W Dai, Y Zheng, T Cai. “Robust dynamic risk prediction with longitudinal studies”. Statistical Theory and Related Fields 2017;1(2):159–170.
• D Agniel, T Cai. “Analysis of multiple diverse phenotypes via semiparametric canonical correlation analysis”. Biometrics 2017;73(4):1254–1265.
• W Dai, M Yang, C Wang, T Cai. “Sequence robust association test for familial data”. Biometrics 2017;73(3):876–884.
• Y Zheng, M Brown, A Lok, T Cai. “Improving efficiency in biomarker incremental value evaluation under two-phase designs”. The Annals of Applied Statistics 2017;11(2):638–654.
• D Agniel, KP Liao, T Cai. “Estimation and testing for multiple regulation of multivariate mixed outcomes”. Biometrics 2016;72(4):1194–1205.
• FH Yong, L Tian, S Yu, T Cai, LJ Wei. “Optimal stratification in outcome prediction using baseline information”. Biometrika 2016;103(4):817–828.
• M Neykov, JS Liu, T Cai. “On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting”. Journal of Machine Learning Research 2016;17(70):1-32.
• Y Shen, T Cai. “Identifying predictive markers for personalized treatment selection”. Biometrics 2016;72(4):1017–1025.
• J Minnier, M Yuan, JS Liu, T Cai. “Risk Classification With an Adaptive Naive Bayes Kernel Machine Model”. Journal of the American Statistical Association 2015;110(509):393–404.
• Y Shen, KP Liao, T Cai. “Sparse kernel machine regression for ordinal outcomes”. Biometrics 2014;71(1):63–70.
• JA Sinnott, T Cai. “Omnibus Risk Assessment via Accelerated Failure Time Kernel Machine Modeling”. Biometrics 2013;69(4):861–873.
• L Parast, T Cai. “Landmark risk prediction of residual life for breast cancer survival”. Statistics in Medicine 2013;32(20):3459–3471.
• L Parast, S Cheng, T Cai. “Landmark Prediction of Long-Term Survival Incorporating Short-Term Event Time Information”. Journal of the American Statistical Association 2012;107(500):1492–1501.

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