Maximin D‐Optimal Designs for Longitudinal Mixed Effects Models

In this article, the optimal selection and allocation of time points in repeated measures experiments is considered. D‐optimal cohort designs are computed numerically for the first‐ and second‐degree polynomial models with random intercept, random slope, and first‐order autoregressive serial correlations. Because the optimal designs are locally optimal, it is proposed to use a maximin criterion. It is shown that, for a large class of symmetric designs, the smallest relative efficiency over the model parameter space is substantial.