Courses
University Courses
Applied Survival Analysis
Spring 2020 – 2025
Provides a survey of statistical methods for time-to-event data arising in medical and industrial settings.
- Kaplan-Meier estimator, log-rank test, Cox proportional hazards model
- Multiple failures, recurrent events, competing risks, joint analysis with longitudinal data, multistate processes, composite endpoints
- Causal inference, machine learning
Emphasizes case studies and data analysis (using R)
Applied Longitudinal Analysis
Spring 2019
Introduces modern statistical methods for longitudinal data, with applications in health sciences, behavioral studies, and beyond.
- Linear mixed-effects models, mean and variance structure
- Marginal models, generalized estimating equations (GEE)
- Generalized linear mixed effects models, growth curve analysis
- Missing data, sample size calculation
Emphasizes modeling and analyzing real-world datasets (using SAS)