| Abstract: | Relationships of power of (Fisher) F tests to expected mean squares, E(MS), in the analysis of variance is discussed. While components of variance in the E(MS) are largely a function of nature, the coefficients associated with them are matters of experimental design. Frequently a different cost is associated with each type of experimental unit represented by the different coefficients. It is possible to maximize power relative to cost by optimal allocation of available resources among various types of experimental units—for example, numbers of Ss, duplicate measures, replicates, etc. A simple index of relative power involving the ratio of the estimated F ratio to F alpha is proposed as useful in choosing the allocation of resources most likely to yield significant results. (PsycINFO Database Record (c) 2010 APA, all rights reserved) |
