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Many studies, such as a study of comparative effectiveness, entail a comparison of the beneficial and adverse effects of multiple K 2 competing therapies. Often, the analysis consists of a comparison of the K groups using an omnibus (T²-like) test for any difference among the groups followed by pairwise comparisons with adjustments for multiple tests.

We evaluate the properties of an analysis strategy in which each group is compared to the average of the others in hopes of establishing the overall superiority (or harm) of at least one of the therapies. Testing of one-versus-others can be accomplished for virtually any model using simple tests, and the type I error probability can be controlled by conducting such tests under the closed testing principle. Testing using linear models, the family of generalized linear models, and Cox proportional hazards models is described with examples.