An Asymptotically Optimal Subclass of Balanced Treatment Incomplete Block Designs for Comparisons with a Control
研究用于估计处理与控制组差异的不完全区组设计，发现一个小子类在最小化同时置信区间长度准则下包含渐近最优设计，可用于轻松构造大型优良设计。
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.