abstract
- 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, focusing on how the choice of α affected the relative probabilities and implied costs of Type I and Type II errors. Using α = 0.05 resulted in implied relative costs of Type I vs Type II errors that were both inconsistent among monitoring end points and also inconsistent with the philosophy of the monitoring program. Using α = 0.05 also resulted in combinations of Type I and II error that were 15-17% larger than those for "optimal" α levels set to minimize Type I and II errors for each study, and 12% of all monitoring tests would have reached opposite conclusions had they used these optimal α levels for decision-making. Thus, if the Canadian EEM program used study-specific optimal α levels, they would reduce the incidence of relevant errors and eliminate inconsistent implied relative costs of these errors. Environmental research and monitoring programs using α = 0.05 as a decision-making threshold should re-evaluate the usefulness of this "one-size-fits-all" approach.