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Abuse of hypothesis testing statistics in ecological risk assessment
Authors:Glenn W. Suter II
Affiliation:Environmental Sciences Division , Oak Ridge National Laboratory , P.O. Box 2008, MS 6038, Oak Ridge, TN, 37831–6038 Phone: (423) 574–7306 Fax: (423) 574–7306 E-mail: swg@ornl.gov
Abstract:Statistical hypothesis testing is commonly used inappropriately to analyze data, determine causality, and make decisions about significance in ecological risk assessment. Hypothesis testing is conceptually inappropriate in that it is designed to test scientific hypotheses rather than to estimate risks. It is inappropriate for analysis of field studies because it requires replication and random assignment of treatments. It discourages good toxicity testing and field studies, it provides less protection to ecosystems or their components that are difficult to sample or replicate, and it provides less protection when more treatments or responses are used. It provides a poor basis for decision‐making because it does not generate a conclusion of no effect, it does not indicate the nature or magnitude of effects, it does not address effects at untested exposure levels, and it confounds effects and uncertainty. Attempts to make hypothesis testing less problematical cannot solve these problems. Rather, risk assessors should focus on analyzing the relationship between exposure and effects, on presenting a clear estimate of expected or observed effects and associated uncertainties, and on providing the information in a manner that is useful to decision‐makers and the public.
Keywords:risk assessment  statistics  causality  inference  hypothesis testing
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