Bradley Jones, BradleyJones, PhD, JMP Principal Research Fellow, SAS
The Custom Design tool in JMP implements the idea of model-oriented design. That is, a custom design maximises the information about a specified model. Designed experiments often have strong symmetry (such as orthogonal columns). This suggests that analytical methods for designed experiments could profitably take advantage of what is already known about their structure. I call this idea design-oriented modelling. Definitive screening designs (DSDs) have a special structure with many desirable properties. They have orthogonal main effects, and main effects are also orthogonal to all second-order effects. DSDs with more than five factors project onto any three factors to enable efficient fitting of a full quadratic model. However, analytical methods for DSDs employ generic tools invented for the regression analysis of observational data. These approaches do not take advantage of all the useful structure that DSDs provide. This talk introduces an analytical approach for DSDs that does take explicit advantage of the special structure of DSDs. To make the methodology clear, I will provide a step-by-step procedure for analysis using specific examples.