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 Interpreting results: P Value

After entering data into a Survival data table in Prism, the analysis is performed automatically. When data for more than one group (data set) is entered, Prism will include tests that compare each group. On the Curve comparison tab of the results sheet, a P value will be reported for each of the tests that Prism performs.

## Interpreting the P value

The null hypothesis for each of the tests that Prism performs is that the survival curves for each group are identical in the overall populations from which subjects in each group were sampled. In other words, if the two groups represent a “treatment” group and a “control” group, the null hypothesis would be that the treatment did not affect survival.

The P value for these tests answers this question:

If the null hypothesis is true, what is the probability of randomly selecting subjects whose survival curves are as different (or more so) than what was actually observed?

If the P value is small enough (smaller than a pre-specified threshold), then we say that the null hypothesis is rejected. Note that the P value is based on comparing entire survival curves, not on comparing only the median survival for each group.

## One-tail P value

Prism always reports a two-tail P value when comparing survival curves. If you would like to report a one-tail P value, you must have predicted which group would present the longer median survival prior to collecting any data. Computing the one-tail P value depends on whether your prediction was correct or not.

If your prediction was correct, the one-tail P value will be half of the two-tail P value

If your prediction was incorrect, the one-tail P value equals 1.0 minus half of the two-tail P value. This value will be greater than 0.50, and you will not reject the null hypothesis that the survival curves are the same