Joint analysis of longitudinal and recurrent event data: A functional regression approach with autoregressive frailty
In Statistical Methods in Medical Research, 35(7), 1463–1479 · 2026
Sy Han (Steven) Chiou
Associate Professor of Statistics
Southern Methodist University
About me
I develop statistical methods and open-source software for survival and recurrent-event data, with applications in public health and clinical research. I am an associate professor in the Department of Statistics and Data Science at Southern Methodist University. My work connects methodological research with practical tools for analyzing complex event histories. Before joining SMU, I held appointments at UT Dallas, Harvard T.H. Chan School of Public Health, and the University of Minnesota Duluth. I am an elected member of the International Statistical Institute.
Interests
- Survival analysis
- Statistical computing
- Environmental applications
- Public health applications
Education
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Ph.D. in Statistics, 2013
University of Connecticut
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B.S. in Statistics, 2008
University of Connecticut
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B.S. in Applied Mathematics, 2008
University of Connecticut
Recent publications
Variable selection for stratified sampling designs in semiparametric accelerated failure time models with clustered failure times
In Journal of Multivariate Analysis · 2026
New 10-year atherosclerosis cardiovascular disease risk score for asian and american indian women service members
In Journals of the American College of Cardiology: Asia · 2026
R package
FunSurv
Functional predictors for recurrent events
Jointly model longitudinal measurements and recurrent events using functional regression with autoregressive frailty.
R package
reReg
Regression for recurrent events
Fit regression models for recurrent events and terminal outcomes, with tools for visualization and simulation.
R package
aftgee
Accelerated failure time models
Fit accelerated failure time models with rank-based estimation and generalized estimating equations.
Research code
reForest
Prediction of recurrent events
Code and examples for global and episode-specific prediction using survival tree ensembles.
Recent courses
STAT 6337
Statistical Analysis II
Syllabus Spring 2026 Junkins Building 0203 TuTh 12:30 pm – 1:50 pm
Contact
For questions about my research, software, or teaching, please email me.
- schiou@smu.edu
- 214 768 2441
- 105 Heroy
- 3225 Daniel, Suite 144, Heroy Building, Dallas TX 75275-0332, USA
- Fall 2026: Thursday, 3:30–5:00 pm