For example, it can be of interest to compare the survival times of two samples of the same product produced in two different locations. The Kaplan-Meier analysis allows you to compare populations, through their survival curves. The first type of data is usually called failure data, or event data, while the second is called censored data. There are three main reasons why a population of individuals or products may evolve: some individuals die (products fail), some other go out of the surveyed population because they get healed (repaired) or because their trace is lost (individuals move from location, the study is terminated, among other reasons). This technique is mostly applied to survival data and product quality data. Kaplan-Meier analysis is used to analyze how a given population evolves with time.
Kaplan-Meier analysis, which main result is the Kaplan-Meier table, is based on irregular time intervals, contrary to the life table analysis, where the time intervals are regular. Kaplan-Meier analysis allows you to quickly obtain a population survival curve and essential statistics such as the median survival time.
The life table analysis method was developed first, but the Kaplan-Meier method has been shown to be superior in many cases. The Kaplan-Meier method, also called product-limit analysis, belongs to the descriptive methods of survival analysis, as does life table analysis.
