Survival analysis in R Programming Language

Biological sciences are the most important application of survival analysis in which we can predict the time for organisms eg. when they will multiply to sizes etc.

Methods used to do survival analysis: 

There are two methods that can be used to perform survival analysis in R programming language: 

  • Kaplan-Meier method
  • Cox Proportional hazard model

Survival Analysis in R

Survival analysis in R Programming Language deals with the prediction of events at a specified time. It deals with the occurrence of an interesting event within a specified time and failure of it produces censored observations i.e incomplete observations. 

Similar Reads

Survival analysis in R Programming Language

Biological sciences are the most important application of survival analysis in which we can predict the time for organisms eg. when they will multiply to sizes etc....

Kaplan-Meier Method

The Kaplan-Meier method is used in survival distribution using the Kaplan-Meier estimator for truncated or censored data. It’s a non-parametric statistic that allows us to estimate the survival function and thus not based on underlying probability distribution. The Kaplan–Meier estimates are based on the number of patients (each patient as a row of data) from the total number of patients who survive for a certain time after treatment. (which is the event)....

Cox proportional hazard model

...