An Asymptotically Optimal Subclass of Balanced Treatment Incomplete Block Designs for Comparisons with a Control
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Incomplete block designs for estimation of treatment-control differences are studied. A class of designs for this purpose, called balanced treatment incomplete block designs, has recently been proposed and studied by several authors. Here, a relatively small subclass of these designs is shown to contain the asymptotically optimal design under the criterion of minimizing the length of simultaneous confidence intervals for treatment-control differences. These results can be used to easily construct good large designs. Some specific finite cases are considered.