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Abstract
A typical agricultural experiment involves comparisons of several treatments at different points in time. The ensuing lack of independence between observations of the same experimental unit may then impair the attainment of statistical significance by the standard analysis of variance, and calls for the application of more powerful methods. This paper addresses one such method, the so-called two-factor experiment with repeated measures on one factor. We discuss the adequacy of this model in the context of three concrete examples drawn from agricultural experimentation.
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