Survival Analysis In R - r - learn r - r programming
- Survival analysis deals with predicting the time when a specific event is going to occur. It is also known as failure time analysis or analysis of time to death.
- For example predicting the number of days a person with cancer will survive or predicting the time when a mechanical system is going to fail.
- The R package named survival is used to carry out survival analysis.
- This package contains the function Surv() which takes the input data as a R formula and creates a survival object among the chosen variables for analysis.
- Then we use the function survfit() to create a plot for the analysis.
r programming survival analysis
- The basic syntax for creating survival analysis in R is −
- Following is the description of the parameters used −
- time is the follow up time until the event occurs.
- event indicates the status of occurrence of the expected event.
- formula is the relationship between the predictor variables.
- We will consider the data set named "pbc" present in the survival packages installed above.
- It describes the survival data points about people affected with primary biliary cirrhosis (PBC) of the liver.
- Among the many columns present in the data set we are primarily concerned with the fields "time" and "status".
- Time represents the number of days between registration of the patient and earlier of the event between the patient receiving a liver transplant or death of the patient.
- When we execute the above code, it produces the following result and chart
- From the above data we are considering time and status for our analysis.
Applying Surv() and survfit() Function
- Now we proceed to apply the Surv() function to the above data set and create a plot that will show the trend.
- When we execute the above code, it produces the following result and chart −
- The trend in the above graph helps us predicting the probability of survival at the end of a certain number of days.