A Remedy for the Overzealous Bonferroni Technique for Multiple Statistical Tests

Abstract

AbstractEcological research often involves multiple statistical tests. It is common practice to employ the Bonferroni technique or its more advanced sequential variant for such multiple tests. Indeed, Moran (Oikos, 100, 2003, 403) found that 13% of ecological papers apply this technique. The seminal paper by Rice (Evolution, 43, 1989, 223) that introduced this technique to the ecological community, is cited to date over 12 000 times. However, these techniques are conservative and some null hypotheses that should be rejected are not. Using order statistics we find that significant results are correlated even when the data consist of independent events. The Bonferroni methods assume independent significant results which results in Type II error with their application. We propose a simple approach, which we term the correlated Bonferroni technique, to rectify this shortcoming, which reduces rejection of significant results. Ecologists may be able to confirm the significance of their results while they are unable to confirm it using the original Bonferroni technique. Researchers may revisit their projects and find that significant results were mistakenly ignored. We provide an Excel file (see supplement) that researchers can easily use. We illustrate the correlated Bonferroni technique with an example.