Environmental pollution impacts: Are p values over-valued?

Abstract

An examination revealed the dominance of the published literature of environmental science by p values. Meanwhile, the use of effect size has been neglected in publications reporting primary data, yet the size of effect is often more informative than p values inference in assessing the effects of pollution on living organisms, comparing susceptibility/resistance among organisms, and ranking pollutants according to their potency, among others. Statistical significance does not necessarily mean biological, practical, or scientific significance, and its use based on (often misinterpreted) p values reflects the average response or effect at average conditions based on an assumed linear model fit to the entire sample. However, pollution impacts and organismal responses are rarely characterized by linear and symmetric features, and dichotomous ‘statistical significance’ based on p values is inadequate to fully describe data and findings. Considering ‘the fallacy of the average’, variance, and differential response of different population percentiles in new studies would provide otherwise wasted biologically, practically, or scientifically significant information. Since p values often inform as to whether some findings warrant further examination, journals should consider mandating the reporting of effect sizes and confidence intervals, together with p values (should they be used), to provide more integrated information regarding pollution impacts. Moreover, replacing ‘statistical significance’ with language of evidence, especially in key components of publications, such as abstracts and conclusions, could help preventing potential misleading of the public and decision and policy makers.