Robustness and efficiency of D-optimal experimental designs in a growth problem

To assess tree growth, for example in diameter, a forester typically measures the trees at regular time points. We call such designs equidistant. In this paper we look at the robustness and efficiency of several experimental designs, using the D-optimality criterion, in a case study of diameter growth in cork oaks. We compare D-optimal designs (unrestricted and replication-free) with equidistant designs. We further compare designs in different experimental regions. Results indicate that the experimental region should be adequate to the problem, and that D-optimal designs are substantially more efficient than equidistant designs, even under parameter mis-specification.