The Analysis of Covariance as a Missing Plot Technique

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Abstract
The covariance analysis provides a general technique for analyzing data from a statistically designed experiment when one or more observations are missing. The technique may be applied to data from an experiment of any statistical design, and furnishes estimates of the missing observations and exact tests of significance with relatively little computational effort. This paper describes the application of the technique when one or several observations are missing. Specific examples given for fractional factorial and split-plot experiments illustrate the computational procedures involved.

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