SCALABLE DECISION RULES FOR ENVIRONMENTAL-IMPACT STUDIES - EFFECT SIZE, TYPE-I, AND TYPE-II ERRORS

Assessments of environmental impacts are being subject to greater scie ntific and legal scrutiny than ever before. The application of traditi onal statistical decision-making criteria to questions of environmenta l impacts has become increasingly inadequate as society demands greate r environmental accountability from economic development. In particula r, impact assessment has inherited a preoccupation with Type I error r ates that has pervaded ecological research, even though Type II errors are often equally severe in impact assessment. Estimation of Type II error rates and specification of critical effect sizes-or the magnitud es of impacts considered important-are mutually dependent. Considerati on of Type II errors, therefore, requires the exact specification of a n hypothesized impact, which is often difficult. Insistence on low rat es of Type I error (e.g., alpha = 0.05) typically means that equivalen t rates of Type II error can be realized only when effect sizes (ES) a re very large or when very many samples are taken. Rather than adherin g to a fixed, arbitrary, critical, Type I error rate, I propose a proc edure by which the critical ES is given primacy. Statistical decision criteria are then selected according to the relative weighting of the perceived consequences of Type I or Type II errors. The critical Type I error rate is set by iteration to some multiple (k) of the estimated potential for Type II error, and the null hypothesis is rejected if t hat (variable) Type I probability is not exceeded. The value of k woul d be determined by the ratio of the consequences (e.g., costs) of Type II and Type I errors. The procedure focuses attention on the magnitud es of impacts considered important, and provides for statistical decis ions based on the a priori consideration of the development and enviro nmental costs of Type I and Type II errors. It also provides incentive for development proponents to support rigorous environmental monitori ng.