The MISER criterion for imbalance in the analysis of covariance

Abstract

This paper describes a new statistical technique for comparing unbalanced experimental designs that will be modeled by the univariate analysis of covariance. We propose treating the imbalance in the design by Minimizing the Inflation of the Standard Error of a contrast (MISER). We also discuss attributing the increased variance caused by imbalance in a design to particular covariates. The effect of implementing the proposed MISER criterion is to generate a design that is sensitive to treatment effect differences. The MISER criterion is applied to a social experiment involving offering cash incentives to induce high quality young men to enlist in the U.S. Army.