User Guide

93
Chapter
10
Kaplan-Meier Survival Analysis
There are many situations in which you would want to examine the distribution of
times between two events, such as length of employment (time between being hired
and leaving the company). However, this kind of data usually includes some censored
cases. Censored cases are cases for which the second event isn’t recorded (for
example, people still working for the company at the end of the study). The Kaplan-
Meier procedure is a method of estimating time-to-event models in the presence of
censored cases. The Kaplan-Meier model is based on estimating conditional
probabilities at each time point when an event occurs and taking the product limit of
those probabilities to estimate the survival rate at each point in time.
Example. Does a new treatment for AIDS have any therapeutic benefit in extending
life? You could conduct a study using two groups of AIDS patients, one receiving
traditional therapy and the other receiving the experimental treatment. Constructing a
Kaplan-Meier model from the data would allow you to compare overall survival rates
between the two groups to determine whether the experimental treatment is an
improvement over the traditional therapy. You can also plot the survival or hazard
functions and compare them visually for more detailed information.
Statistics. Survival table, including time, status, cumulative survival and standard
error, cumulative events, and number remaining; and mean and median survival time,
with standard error and 95% confidence interval. Plots: survival, hazard, log survival,
and one minus survival.
Data. The time variable should be continuous, the status variable can be categorical or
continuous, and the factor and strata variables should be categorical.