In industrial experimentation, there is growing interest in studies that span more than one processing step. Convenience often dictates restrictions in randomization in passing from one processing step to another. When the study encompasses three processing steps, this leads to split-split-plot designs. We provide an algorithm for computing D-optimal split-split-plot designs and several illustrative examples.

, , , , ,
hdl.handle.net/1765/19555
ERIM Article Series (EAS)
Biometrika
Erasmus Research Institute of Management

Jones, B, & Goos, P.P. (2009). D-optimal design of split-split-plot experiments. Biometrika, 96(1), 67–82. Retrieved from http://hdl.handle.net/1765/19555