Introduction to Survival Analysis using R: Theory and Practice

 

 

 

 

 

 

 

 

 

 

 

 

 

Prof. Dr. Roel Braekers.during the training

This  five days course introduces the basic concepts of Survival analysis. Hereby we explain the commonly used methods to estimate a survival function and to compare different survival functions in a non-parametric way. Next, we introduce the Cox’s regression model to study the influence of covariates on the hazard function in a semi-parametric way. Finally, we finished with the introduction of different parametric distributions for the survival function and consider the accelerated failure time model to investigate how covariates change this survival function. As extra, we give an introduction into multivariate survival analysis by looking at frailty and copula models.

 

Instructor :
Prof. Dr. Roel Braekers (Universiteit Hasselt, Belgium)

Objectives

This workshop aims at giving a broad introduction into the research field of survival analysis. Hereby basic concepts and methods of survival analysis will be introduced and explained. Together with this theoretical background, statistical tools are introduced to analyze practical data problems within survival analysis using R software.

The participants are expected:

  • to get familiar with basic concepts of survival analysis
  • to understand different nonparametric estimators for the survival function and to compare different survival functions using the log-rank test
  • to understand the semi-parametric Cox’s regres-sion model in the investigation of the influence of covariates on the hazard function
  • to get acquainted with parametric distributions and regression models for the survival function
  • to get a brief introduction into multivariate survival analysis
  • to get familiar with the statistical procedures in R in the analysis of real life data examples.

Software

In this workshop, we use the software package R for the different statistical analyses.

R is available as Free Software and runs under Windows and Macintosh. It can be downloaded at https://cran.rproject.org/. It is recommended that participants install the software beforehand.

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