Survival Analysis is a sub discipline of statistics. It actually has several names. In some fields it is called event–time analysis, reliability analysis or duration analysis. R is one of the main tools to perform this sort of analysis thanks to the survival package.
In this course you will learn how to use R to perform survival analysis. To check out the course content it is recommended to take a look at the course curriculum. There are also videos available for free preview.
The course structure is as follows:
We will start out with course orientation, background on which packages are primarily used for survival analysis and how to find them, the course datasets as well as general survival analysis concepts.
After that we will dive right in and create our first survival models. We will use the Kaplan Meier estimator as well as the logrank test as our first standard survival analysis tools.
When we talk about survival analysis there is one model type which is an absolute cornerstone of survival analysis: the Cox proportional hazards model. You will learn how to create such a model, how to add covariates and how to interpret the results.
You will also learn about survival trees. These rather new machine learning tools are more and more popular in survival analysis. In R you have several functions available to fit such a survival tree.
Courses : 4
Specification: Survival Analysis in R