Statistical notes for clinical researchers: effect size

Abstract

In most clinical studies, p value is the final result of data analysis. A small p value is interpreted as a significant difference between the experimental group and the control group. However, reporting p value is not enough to know the actual difference. Problem of p value is that it depends on the sample size, n. Even a trivial meaningless difference can result in an extremely small p value when sample size is large. To make up this weak point, we need to report the 'effect size' as well as the p value. Effect size is a simple way to show the actual difference, which is independent of the sample size.

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