Unified power analysis for t-tests through multivariate hypotheses.

Abstract

In this chapter, we present a strategy for performing power analyses that is applicable to the broad range of methods subsumed by the classical normal-theory univariate or multivariate general linear models. First, we introduce the requisite concepts of statistical power using concepts from the familiar t-test to compare two independent group means. Second, we proceed to the comparison of two correlated means (matched-pairs problem) and on to the one-way analysis of variance (ANOVA) with contrasts for a completely randomized design. Third, we develop power analysis for the univariate general linear model, thus providing a broad range of applications. We illustrate this with an analysis of covariance (ANCOVA) problem that has unequal distributions of the covariate's values