The Powers and Strengths of Tests for Multinomials and Contingency Tables

Abstract The strength of a significance test is defined as a weighted average of the power especially if the weights are a prior density. The concept is a compromise between Neyman-Pearsonian and Bayesian methods and is applied to tests for multinomial equiprobability and for no association in contingency tables. The differences of the power functions of two criteria, X 2 and G, are illustrated for the trinomial, where G arose earlier from a partially Bayesian approach. Other methods for apprehending power functions of several variables are discussed. For 2 × 2 contingency tables with equal row or column totals the power and strength functions of several statistics are equal.