Optimal Selection Criteria for Regular Fractional Factorial Designs
by
Hegang H. Chen
Division of Biostatistics and Bioinformatics, University of Maryland, 660 W. Redwood St., HH 113, Baltimore, MD 21201

Fractional factorial designs have a long history of successful use in scientific investigations. Resolution (Box and Hunter (1961)) and its refinement, minimum aberration (Fries and Hunter (1980)), are commonly used criteria for selecting regular fractional factorial designs. Both of these criteria are based on wordlength patterns of the designs. Cheng, Steinberg and Sun (1999) showed that minimum aberration criterion is a good surrogate for some model-robustness criteria such as maximum estimation capacity. Recently, the concept of estimation index (Chen and Cheng (2004)) was proposed to help assess a fractional factorial design's capability to estimate factorial effects. The estimation index provides some insight into when a design is capable of entertaining the largest number of lower-order effects. In this talk, the relationships among estimation index, resolution, minimum aberration and estimation capacity will be discussed. In addition to deriving some general results of relationship among various criteria, I will demonstrate how to combine information on wordlength pattern and estimation index to study the estimation capability of regular fractional factorial designs. This talk is based on joint work with Prof. Ching-Shui Cheng.

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Date received: September 11, 2005