## Tutorial: Survival Analysis in R |

Goals:

This tutorial presents a brief description including methodological aspects and examples on how to perform a Survival Analysis in R.

Detailed outline:

- Estimating survival and hazard functions.
- Comparison of survival curves.
- The proportional hazard (Cox) model (including model with fixed covariates and covariates varying in time).
- The Aalen additive model.
- Parametric survival models.
- Introduction to Frailty models.
- Introduction to multivariate survival models (Recurrent events, Competing risks, multi-state models).

Justification:

Although survival is the most used package in survival analysis, there are useful tools in other packages. R has a wide list of resources for performing survival analysis, including some specific packages in the CRAN website: bayesSurv, cmprsk, dblcens, eha, emplink, frailtypack Icens, intcox, kinship, Kmsurv, msm, musa, relsurv, smoothSurv, subrayes, survival, survnnet, survrec and zicount, and the general package Hmisc. There are also other functions that work with certain models in survival models, such as addreg for the Aalen's additive model. The purpose of this course is to present many useful tools to perform a Survival Analysis, including some methodological aspects and examples.

Background knowledge:

A basic knowledge in survival analysis is preferred, but it is not necessary.

useR-2006@R-project.org