March 2: William Li and Christopher Nachtsheim, University of Minnesota

UNIVERSITY OF MINNESOTA

SEMINAR

School of Statistics
College of Liberal Arts

Model Robust Fractional Factorial Designs

William Li and Christopher J. Nachtsheim
Carlson School of Management
University of Minnesota

Thursday, March 2, 2000
4:00-5:00 PM, Room 133 Physics
Social at 3:30 PM in Room 300 Ford Hall

Abstract

In industrial experimentation, experimental designs are frequently constructed to estimate all main effects and a small number of pre-specified interactions. The robust product design literature is replete with such examples. The requirement that the experimenter knows which interactions are likely to be active in advance is a major limitation of this approach. In this presentation, we develop a class of balanced designs that can be used for estimation of main effects and any combination of up to g interactions, where g is specified by the user. We view this as an issue of model robust design: we construct designs that are highly efficient for all models involving main effects and g (or fewer) interactions. We compare the performances of these designs with the standard alternatives from the class of maximum resolution fractional factorial designs for a number of criteria. The comparison reveals that the new designs are surprisingly robust to model misspecification, something that is generally not true for maximum resolution fractional factorial designs. This robustness comes at a price: the new designs are frequently not orthogonal. We demonstrate, however, that the loss of orthogonality is, in general, quite small.