Using false discovery rates for multiple comparisons in ecology and evolution

Abstract

Summary 1. Ecologists and evolutionary biologists often need to simultaneously evaluate the significance of multiple related hypotheses. Multiple comparisons need to be corrected to avoid inappropriately increasing the number of null hypotheses that are wrongly rejected. The traditional method of correction involves Bonferroni‐type multiple comparison procedures which are highly conservative, tending to increase the number of wrong rejections of true hypotheses as the number of hypotheses being simultaneously tested increases. 2. Newer procedures which are based on False Discovery Rates and which do not suffer the same loss of power as traditional methods are described. Algorithms and spreadsheet‐based software routines for three procedures which are especially useful in ecology and evolution are provided. 3. The strengths and potential pitfalls of FDR‐based analysis and of presenting results as FDR‐adjusted P ‐values are discussed with reference to traditional methods such as the sequential Bonferroni correction. 4. FDR‐based multiple comparison procedures should be more widely adopted because they are often more appropriate than traditional methods for identifying truly significant results.