Conditional Optimal Design in Three- and Four-Level Experiments

The precision of estimates of treatment effects in multilevel experiments depends on the sample sizes chosen at each level. It is often desirable to choose sample sizes at each level to obtain the smallest variance for a fixed total cost, that is, to obtain optimal sample allocation. This article extends previous results on optimal allocation to four-level cluster randomized designs and randomized block designs. It also introduces the idea of constrained optimal allocation, where the sample size at one or more levels is fixed by considerations other than cost or sampling variation. Explicit formulas are given for constrained optimal allocation in three- and four-level designs.