We plan to identify optimal and efficient statistical designs in several commonly used scientific studies. These areas include, but not limite to, two-level factorial designs for main effects and selected two-factor interactions; resolution III and more two-level fractional factorial designs with (weak) minimum aberration; repeated measurements designs for comparative bioavaliability studies. Inference based on data collected via poorly designed studies is generally misleading and could be invalid altogether. Good science calls for good data and good data can come only through statistically designed studies. This proposal plans to identify and build statistically efficient designs/per unit cost so that better data can be collected and valid scientific inference can be made. Our discoveries will have immediate applications to many areas of scientific studies including medicine and engineering. We plan to solve design problems which have been posed to us by scientists at US FDA, and many US industries.
