Factorial Analysis of Variance

Abstract

A common task in research is to compare the average response across levels of one or more factor variables. Examples of factor variables are income level of two regions, nitrogen content of three lakes, or drug dosage. The factorial analysis of variance compares the means of two or more factors. F tests are used to determine statistical significance of the factors and their interactions. The tests are non-directional in that the null hypothesis specifies that all means are equal, and the alternative hypothesis simply states that at least one mean is different. This PASS module performs power analysis and sample size estimation for an analysis of variance design with up to three fixed factors.