It all started with this article by Malcolm Gladwell in The New Yorker, which begins thus:
In the world of cancer research, there is something called a Kaplan-Meier curve, which tracks the survival of patients in the trial of an experimental drug. In its simplest form, it consists of two lines. The first follows the patients in the “control arm,” the second the patients in the “treatment arm.” In most cases, those two lines are virtually identical. But every now and again the patients in the treatment arm will live longer than the patients in the control arm, and the two lines on the Kaplan-Meier will diverge.Curious, I went looking for an illustration and found this helpful introductory article in Wikipedia
The Kaplan–Meier estimator, also known as the product limit estimator, is an estimator for estimating the survival function from life-time data. In medical research, it is often used to measure the fraction of patients living for a certain amount of time after treatment. In economics, it can be used to measure the length of time people remain unemployed after a job loss. In engineering, it can be used to measure the time until failure of machine parts. In ecology, it can be used to estimate how long fleshy fruits remain on plants before they are removed by frugivores. The estimator is named after Edward L. Kaplan and Paul Meier.
Intrigued by the medical, economic, engineering, and ecological applications of the Kaplan-Meier, I set out to get some data and learn how to plot the curve in MS Excel. I found this tutorial, How to Construct a Step Chart, on tushar-mehta.com.
Since my main interest circles back to cancer research, I went looking for more cancer-specific information and found the Cancer Guide
Armed with my own lab results, I had the ability to plot my personal Kaplan-Meier Curve. Fortunately, the data told a reassuring story.
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