This repository contains the materials associated to my short course on parametric models for the analysis of survival data. The material covers parametric models for Overall and Relative survival, as well as several software tools to implement these sorts of models.
Course length: 3-4 hours.
The slides for Lecture I can be found at Lecture I.
Tha aims of this lecture are:
- To describe the aims of survival analysis (overall survival).
- To describe parametric approaches to estimate the survival function.
- To describe two regression models: PH and AFT.
- To present software tools for survival analysis and a real data example.
- To discuss other parametric, semiparametric and non parametric alternatives.
Related R packages include: HazReg and survival.
See also Example: no covariates, and Example: Regression.
The slides for Lecture II can be found at Lecture II.
The aims of this lecture are:
- To introduce the relative survival framework.
- To introduce a general hazard structure.
- To present an application in cancer epidemiology.
- To discuss a challenge in the relative survival framework.
Related R packages include: HazReg, GHSurv, GJRM, and SimLT.
See also: Parametric Excess Hazard Estimation: Proportional Hazards, and Parametric Excess Hazard Estimation: General Hazards, The Cox Proportional Hazards Model .