Survival Analysis

Course description

Requirements: Programming skills with R, e.g. course Introduction to R and basic knowledge of regression models and hypothesis testing, e.g. course Introduction to Statistics. Basic knowledge on applying ggplot2 functions is advantageous but not mandatory (e.g. course Advanced Graphics with R).

Your profit: The participants will be taught the theoretical backgrounds on survival analysis and how to apply them in R. They will learn when to apply survival analysis, what survival analysis method to use in different situations and how to visualize and interpret the results of survival analysis methods. This includes Kaplan-Meier estimation of the survival curve and Cox Proportional Hazards model. Finally, parametric regression models for survival analysis are presented. All topics are accompanied with examples and hands-on exercises in R. Accompanying packages in R for survival analysis will be introduced. 

Topics: This course on survival analysis covers three different parts:

  • Introduction to survival analysis: This includes general assumptions, types of data, censoring, survival time, survival time as a function.
  • Non-parametric estimation of the survival function. This includes Kaplan-Meier estimation of the survival function, visualization of the survival curve, comparison of survival curves and Kaplan-Meier estimation in R.
  • Cox proportional hazards model: This includes when to apply Cox models, model specifications and assumptions, model inference, interpretation of the results of the Cox models, testing the model assumptions and how to run Cox models in R.
  • Parametric regression models: AFT models: Weibull regression, model specifications and assumptions, model inference, interpretation of the results of the Weibull model, testing the model assumptions and how to run Weibull models in R.

Methods: The course consists of theoretical lessons on survival analysis methods, how to apply survival analysis methods and how to visualize survival curves in R. Theoretical lessons will be followed by hands-on examples with best-practice solutions in R. During the Corona-pandemic the course is held as an online course. Please consider the following constraints:

  • It will be held online via the software Zoom.
  • Please check before hand on zoom.us/test whether your computer is compatible with the tool. (No registration necessary, but you have to download some tools)
  • A stable internet connection is absolutely necessary, optimal would be a LAN access.
  • You do NOT need to have a microphone or camera, since we offer a written chat interaction from your side. To avoid breaking down IT we would anyway ask you to shut down the camera and the microphone.

Duration: 2 Days

Language: English

Materials:

  • Material for the course will be found here*.
  • Please be aware that the materials will be updated shortly before the next course.

Dates and Application: You can check the current dates and whether the courses are already fully booked here*.
Please apply via the forms of the HR Development department*

 

 * Links marked with * are only available for HMGU staff.