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Plackett Burman designs are used to estimate main effects because the columns assigned main effects are mutually orthogonal. However, correlations between estimates of a main effect column and a two-factor interaction column are not orthogonal in general. There are variations in the magnitude of correlation depending on the size of Plackett Burman design. For example, correlation coefficients between a main effect and a two-factor interaction are either 0 or ±0.33 in Plackett Burman design N=12. However, most of them are ±0.2 and some of them are 0.6 in Plackett Burman design N=20. When a correlation coefficient between main effects and two-factor interactions is significantly large, analysis results may be depart from the true status. Therefore, in this study, we comprehensively describe correlation coefficients between a main effect and a two-factor interaction for all designs proposed by the Plackett and Burman designs such that N=8,...,100. In addition, for designs that have large correlation coefficients, they are classified according to how to construct a design table and examined in detail. We describe certain rules in combination of a main effect and a two-factor interaction with large correlation coefficient. We also show how to construct designs that avoids large correlation based on the rules.
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OISHI et al. (2021) studied this question.
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