| Week |
Course Content |
| Week 1 |
Introduction to Event-History Data Analysis |
| Week 2 |
Parametric models |
| Week 3 |
Counting process and martingale theory |
| Week 4 |
Kaplan-Meier estimation and several other methods for estimating the survivor function |
| Week 5 |
Nonparametric two-sample tests；
Log rank and weighted logrank tests.
|
| Week 6 |
Students’ presentation for data analysis.
|
| Week 7 |
Cox proportional hazards model and partial likelihood inference； |
| Week 8 |
Cox regression versus Weibull regression: an example with real-world data analysis |
| Week 9 |
Cox model with cure fraction (or nonsusceptibility)；
Applications of Cox model |
| Week 10 |
Stratified proportional hazards (SPH) model；
nested case－control study |
| Week 11 |
Recurrent event models；
Regression diagnostics |
| Week 12 |
Students’ presentation for data analysis. |
| Week 13 |
A Review of the Cox model，its validation and some variants，Additive risk model. |
| Week 14 |
Analysis of Competing Risks；
(18) Joint Modeling for survival data with repeated measurements |
| Week 15 |
Statistical Inference for Heteroscedastic Survival Models |
| Week 16 |
Students’ presentation for data analysis.
自主學習週（教學影片） |
self-directed
learning |
03.Preparing presentations or reports related to industry and academia.
|