The Minimum Detectable Difference (MDD) Concept for Establishing Trust in Nonsignificant Results: A Critical Review

Current regulatory guidelines for pesticide risk assessment recommend that nonsignificant results should be complemented by the minimum detectable difference (MDD), a statistical indicator that is used to decide whether the experiment could have detected biologically relevant effects. We review the statistical theory of the MDD and perform simulations to understand its properties and error rates. Most importantly, we compare the skill of the MDD in distinguishing between true and false negatives (i.e., type II errors) with 2 alternatives: the minimum detectable effect (MDE), an indicator based on a post hoc power analysis common in medical studies; and confidence intervals (CIs). Our results demonstrate that MDD and MDE only differ in that the power of the MDD depends on the sample size. Moreover, although both MDD and MDE have some skill in distinguishing between false negatives and true absence of an effect, they do not perform as well as using CI upper bounds to establish trust in a nonsignificant result. The reason is that, unlike the CI, neither MDD nor MDE consider the estimated effect size in their calculation. We also show that MDD and MDE are no better than CIs in identifying larger effects among the false negatives. We conclude that, although MDDs are useful, CIs are preferable for deciding whether to treat a nonsignificant test result as a true negative, or for determining an upper bound for an unknown true effect.Environ Toxicol Chem2020;00:1-15. (c) 2020 The Authors.Environmental Toxicology and Chemistrypublished by Wiley Periodicals LLC on behalf of SETAC

Assessment of risk of insect-resistant transgenic crops to nontarget arthropods

An international initiative is developing a scientifically rigorous approach to evaluate the potential risks to nontarget arthropods (NTAs) posed by insect-resistant, genetically modified (IRGM) crops. It adapts the tiered approach to risk assessment that is used internationally within regulatory toxicology and environmental sciences. The approach focuses on the formulation and testing of clearly stated risk hypotheses, making maximum use of available data and using formal decision guidelines to progress between testing stages (or tiers). It is intended to provide guidance to regulatory agencies that are currently developing their own NTA risk assessment guidelines for IRGM crops and to help harmonize regulatory requirements between different countries and different regions of the world