Contrast Analysis

A standard analysis of variance (a.k.a. anova) provides an F -test, which is called an omnibus test because it reflects all possible differences between the means of the groups analyzed by the anova. However, most experimenters want to draw conclusions more precise than “the experimental manipulation has an effect on participants’ behavior.” Precise conclusions can be obtained from contrast analysis because a contrast expresses a specific question about the pattern of results of an anova. Specifically, a contrast corresponds to a prediction precise enough to be translated into a set of numbers called contrast coefficients which reflect the prediction. The correlation between the contrast coefficients and the observed group means directly evaluates the similarity between the prediction and the results.