Yifei Sun, PhD
- Associate Professor of Biostatistics
On the web
Overview
Dr. Sun's substantive area of research is statistical and machine learning methods related to time-to-event outcomes and longitudinal measurements. She has developed nonparametric and semiparametric approaches to analyze marked recurrent event processes, where longitudinal measurements are observed at the occurrence of recurrent events (e.g., clinical visits) and a dependent terminal event (e.g., death), precludes the occurrence of recurrent events. She has also developed statistical methods to deal with left truncation bias in survival analysis. Her recent works include decision tree learning for dynamic prediction of time-to-event outcomes and event history analysis using electronic health records data. Besides the methodological research, Dr. Sun works closely with clinicians and epidemiologists on various research areas, including coronavirus disease 2019, Alzheimer’s disease, and infectious diseases.
Academic Appointments
- Associate Professor of Biostatistics
Credentials & Experience
Education & Training
- BS, 2010 Zhejiang University
- PhD, 2015 Johns Hopkins University
Research
Research Interests
- Biostatistical Methods
- Data integration
- Longitudinal methods
- Statistical Machine Learning
- Survival Analysis
Selected Publications
Sun Y, Chiou SH, McGarry M, Huang C-Y (2023). Dynamic risk prediction triggered by intermediate clinical events using survival tree ensembles. Annals of Applied Statistics. 17(2): 1375-1397.
Sun Y, He X, Hu J. An omnibus test for treatment effects when many subgroups are generated via data partitioning (2022). Annals of Applied Statistics. 16(4): 2266-2278.
Sun Y, Chiou SH, Marr KA, Huang C-Y (2022). Statistical inference for the shape and size indexes of counting processes. Biometrika. 109(1):195-208.
Sun Y, McCulloch CE, Marr KA, and Huang C-Y (2021). Recurrent events analysis with data collected at informative clinical visits in electronic health records. Journal of the American Statistical Association. 116: 594-604.
Sun Y, Chiou SH, Wang M-C (2020). ROC-Guided survival trees and ensembles. Biometrics. 76:1177-1189.
Sun Y, Qin J, and Huang C-Y (2018). Missing information principle: a unified approach for general left-truncated and/or right-censored survival data problems.Statistical Science, 33:261-276.
Sun Y, Chan G, and Qin J (2018). Simple and fast overidentified rank estimation for right-censored length-biased data. Biometrics, 74: 77-85.
Sun Y, Huang C-Y and Wang M-C (2017). Nonparametric benefit-risk assessment using marker process in the presence of a terminal event. Journal of the American Statistical Association, 112(518): 826-836.
Sun Y and Wang M-C (2017). Evaluating utility measurement with recurrent marker processes in the presence of competing terminal events. Journal of the American Statistical Association, 112(518): 745-756.
Sun Y, He X, Hu J. An omnibus test for treatment effects when many subgroups are generated via data partitioning (2022). Annals of Applied Statistics. 16(4): 2266-2278.
Sun Y, Chiou SH, Marr KA, Huang C-Y (2022). Statistical inference for the shape and size indexes of counting processes. Biometrika. 109(1):195-208.
Sun Y, McCulloch CE, Marr KA, and Huang C-Y (2021). Recurrent events analysis with data collected at informative clinical visits in electronic health records. Journal of the American Statistical Association. 116: 594-604.
Sun Y, Chiou SH, Wang M-C (2020). ROC-Guided survival trees and ensembles. Biometrics. 76:1177-1189.
Sun Y, Qin J, and Huang C-Y (2018). Missing information principle: a unified approach for general left-truncated and/or right-censored survival data problems.Statistical Science, 33:261-276.
Sun Y, Chan G, and Qin J (2018). Simple and fast overidentified rank estimation for right-censored length-biased data. Biometrics, 74: 77-85.
Sun Y, Huang C-Y and Wang M-C (2017). Nonparametric benefit-risk assessment using marker process in the presence of a terminal event. Journal of the American Statistical Association, 112(518): 826-836.
Sun Y and Wang M-C (2017). Evaluating utility measurement with recurrent marker processes in the presence of competing terminal events. Journal of the American Statistical Association, 112(518): 745-756.