When designing measurement studies, one generally needs to consider two statistical issues: power and measurement error. The mean error variance-covariance component is introduced as an estimate that takes into account both of these statistical issues. This article presents a methodology for minimizing the mean error variance-covariance component in studies with resource constraints. The method is illustrated using a one-facet multivariate design, and extensions to other designs are discussed.
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