The Kaplan-Meier product-limit estimator (KMPLE) is commonly
used in medicine, epidemiology, and reliability, but it can
be used in any application in which there is time-to-event
data with random right censoring.
Here is one example. Let's say you want to determine the
probability distribution of the lifetime of an airline.
Some airlines have failed (like Pan Am, which was founded
in 1927 and ceased operations in 1991, constituting an observed
lifetime of 64 years). But other airlines are still
operating (like Delta Airlines, which was founded in 1925
and is still operating, constituting a right-censored time of
98 years). The KMPLE can combine these two types of
observations to form a point estimate of the survivor function,
which is one minus the cumulative distribution function.
To extend the application a bit further, you might want
to know whether discount airlines have shorter lifetimes
than the larger carriers. In this case you could plot
the KMPLE of the lifetimes of the larger airlines and the
KMPLE of the lifetimes of the discount airlines on the same
set of axes, then use the log rank test to see if there is
a statistically significant difference between the two
survivor function estimates.
So to answer your question more directly, yes, the KMPLE
is appropriate for use in business applications.
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Lawrence Leemis
Professor of Mathematics
College of William and Mary
Williamsburg VA
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