Some results on multi-level factorial designs with dependent observations

Abstract

In many situations, observations in factorial experiments may be dependent. Run orders are then needed that result in efficient estimates of contrasts of interest. The theory is reasonably well understood for two-level designs under one-dimensional dependence. In this paper, we extend some results to multi-level factorial designs under one-dimensional dependence.