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Tips for Analyzing Nonregular Fractional Factorial Experiments
Summary: [This abstract is based on the authors' abstract.] Plackett-Burman designs and other two-level nonregular fractional factorial designs are popular for identifying the active factors from a large list of experimental factors. Data analysis for these designs is straightforward if interactions can be safely ignored. However, rather than viewing interactions as a hazard, methods have recently been proposed to identify and estimate active interaction effects via nonregular factorial designs. The purpose of this article is to suggest approaches that the author has found useful and to caution against unrealistic attempts for finding many interactions. If interactions are anticipated, the use of designs with more runs than double the number of factors is strongly encouraged.
- Topics: Software and Technology (for statistics, measurement, analysis)
- Keywords: Regression tree, Hierarchical model, Multiple regression, Fractional factorials, Fractional factorial design, Interactions, Orthogonal array (OA), Alias, Plackett and Burman designs, Design of experiments (DOE), Estimation
- Author: Mee,Robert W.
- Journal: Journal of Quality Technology