**Learning objectives**

- Define proportional hazards
- Perform and interpret Cox proportional hazards regression
- Define time-dependent covariates and their use
- Identify the differences between parametric and semi-parametric survival models
- Identify situations when a parametric survival model might be useful

**Outline**

- Review of survival and hazard functions
- The Cox proportional hazards model
- interpretation and inference
- what are proportional hazards
- when hazards aren’t proportional

- Parametric vs semi-parametric survival models

- Vittinghoff sections 6.1-6.2, 6.4

**Learning Objectives**

- Fit a Cox proportional hazard model
- Create a stratified Kaplan-Meier plot
- Fit exponential and Weibull accelerated failure time models
- Fit a model using strata and a time-dependent covariate
- Create a DAG using dagitty

**Exercises**

- Fit a Cox proportional hazard model to the Leukemia 6 MP clinical trial dataset
- Create a stratified Kaplan-Meier plot
- Fit exponential and Weibull accelerated failure time (AFT) models
- Fit a stratified coxph model with a time-dependent covariate using an example from ?coxph
- Draw a DAG starting from dagitty.net and re-create it in R