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Null hypothesis significance testing has been under attack in recent years, partly owing to the arbitrary nature of setting α (the decision-making threshold and probability of Type I error) at a constant value, usually 0.05. If the goal of null hypothesis testing is to present conclusions in which we have the highest possible confidence, then the only(More)
Assessments of potential exposure to fullerenes and their derivatives in the environment are important, given their increasing production and use. Our study focused on fate processes that determine the movement and bioavailability of fullerenes in soil. We evaluated the sorption, biodegradation, and plant uptake of C60 fullerene using (14)C-labeled C60(More)
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(More)
Using the traditional α = 0.05 significance level for null hypothesis significance tests makes assumptions about relative costs of Type I vs relevant Type II errors and inflates their combined probabilities. We have examined the results of 1254 monitoring tests conducted under the Canadian Environmental Effects Monitoring (EEM) program from 1992 to 2003,(More)
Concentrations of glyphosate observed in the environment are generally lower than those found to exert toxicity on aquatic organisms in the laboratory. Toxicity is often tested in the absence of other expected co-occurring contaminants. By examining changes in the phytoplankton and zooplankton communities of shallow, partitioned wetlands over a 5 month(More)
Laboratory and mesocosm experiments have demonstrated that some glyphosate-based herbicides can have negative effects on benthic invertebrate species. Although these herbicides are among the most widely used in agriculture, there have been few multiple-stressor, natural system-based investigations of the impacts of glyphosate-based herbicides in combination(More)
Transcriptomic approaches (microarray and RNA-seq) have been a tremendous advance for molecular science in all disciplines, but they have made interpretation of hypothesis testing more difficult because of the large number of comparisons that are done within an experiment. The result has been a proliferation of techniques aimed at solving the multiple(More)
Setting optimal significance levels that minimize Type I and Type II errors allows for more transparent and well-considered statistical decision making compared to the traditional α = 0.05 significance level. We use the optimal α approach to re-assess conclusions reached by three recently published tests of the pace-of-life syndrome hypothesis, which(More)