title: Statistical reporting deficiencies in environmental toxicology.
abstract: Null hypothesis significance testing is one of the most widely used forms of statistical testing in environmental toxicology. In this short communication, the authors show that the reporting of statistical information when using null hypothesis significance testing is frequently inadequate in environmental toxicology research. The authors demonstrate this by analyzing the statistical information reported for papers employing t tests or analyses of variance in the Environmental Toxicology section of Environmental Toxicology and Chemistry in 2010, which comprised 68% of papers published by this journal in that year. Of these papers, 60% fail to report exact p values, 85% fail to provide degrees of freedom, and 90% fail to report critical effect sizes. Statistical power was reported in only <2% of the published papers. The insufficient provision of statistical information makes interpretation of study results by reviewers and readers difficult. Consistently reporting exact p values with degrees of freedom, considering and explicitly stating biologically relevant critical effect sizes, and reporting statistical power associated with nonsignificant results would be easy to implement and would promote scientific progress in environmental toxicology through increased statistical transparency.
authors.affiliation: Department of Natural Resources and the Environment/Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, Connecticut, USA. thijs.bosker@uconn.edu
authors.forename: Thijs
authors.initials: T
authors.lastname: Bosker
authors.forename: Joseph F
authors.initials: JF
authors.lastname: Mudge
authors.forename: Kelly R
authors.initials: KR
authors.lastname: Munkittrick
mesh_terms: D054750:Ecotoxicology / Q000379:methods* / Q000706:statistics & numerical data; D004784:Environmental Monitoring / Q000379:methods*; D011643:Publishing; D012106:Research; D012107:Research Design; D013223:Statistics as Topic
keywords: Biostatistics; Experimental design; Statistics