The Choice of an Error Term in Analysis of Variance Designs

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Abstract
This article presents a survey of the assumptions which may be made in variance designs, a description of the mathematical models which reflect these assumptions, and a discussion of the ways in which various experimental conditions affect the choice of an error mean square. Particular emphasis is laid upon the principles, purposes, and dangers of pooling error mean squares in order to raise the power of a test. Specific recommendations are made for the rules of procedure for pooling (under various conditions) which produce tests with optimum power and error characteristics.

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