The Kaplan Meier Estimate in Survival Analysis

Abstract

Kaplan-Meier is a statistical method used in the analysis of time to event data. Time to event means the time from entry into a study until a particular event, for example onset of illness. This method is very useful in survival analysis as it is used by the researchers to determine and/or analyze the patients or participants who lost to follow up or dropped out of the study, those who developed the disease of interest or survived it. It is also used to compare two groups of subjects such as a control group, the one that is given placebo and the other treatment group that is the one given the genuine drug. The method is not only applicable to the fields of public health, medicine and epidemiology, but it is also useful in other disciplines such as engineering, economics, among others. Most of the studies that use Kaplan Meier estimate are longitudinal in nature like a cohort study. Examples of studies that Kaplan-Meier estimate can be applicable include death times of kidney transplant patients, times to infection for burn patients and times to death for a breast-cancer trial. A fictive data was created concerning the treatment and control groups who were given Drug A and placebo respectively. The participants in each these two groups are ten and they were followed for 2 years (24 months). A survival table and Kaplan-Meier estimate curve were generated from the SPSS software using the fictive data and these were used to analyze the 24 month study.