Tutorial on Introduction to biostatistics
Survival analysis is a form of time to event analysis. In other words it is defined as measuring the time between an origin point and an end point, often the end point will be taken as death of the patient, occurrence of symptoms or disease onset in clinical research.
Aims of survival analysis may be to estimate survival, compare survival times between two groups or know the relationship of the explanatory variables to the survival time.
Survival analysis involves concepts of censoring in estimating the survival times.
Censoring is defined as study of incomplete observations of the survival time. The following are the types of censoring used in the survival analysis.
Some individuals may not be observed for the full time to failure, e.g. because of loss to follow-up, drop out from the study and termination of the study
This occurs when we do not know the exact time of failure, but rather have data on two time points between which the event occurred.
This occurs when some subjects have a delayed entry into the study.
Methods in Survival Analysis
Kaplan Meier Curve
This curve is used to estimate the survival time and also interpret and compare the two groups survival times. An example is show below:
Cox regression model:
It is used to assess the relation between the explanatory variables and survival times.