This paper describes a new computer-intensive statistical technique for comparing unbalanced experimental designs that will be modeled by the univariate analysis of covariance. It proposes treating the imbalance in the design by Minimizing the Inflation of the Standard Error of a contrast (MISER). It provides results for both the standard Gauss-Markov model (constant error variance) and the model with heteroscedasticity. It also discusses the problem of 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 has great sensitivity to treatment effect differences. The MISER criterion is applied to the Department of Defense's Enlistment Bonus Test, involving offering cash incentives to induce high quality young men to enlist in the U.S. Army.
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