Polynomial Regression with Response Surface Analysis: A Powerful Approach for Examining Moderation and Overcoming Limitations of Difference Scores
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Polynomial regression with response surface analysis is a sophisticated statistical approach that has become increasingly popular in multisource feedback research (e.g., self-observer rating discrepancy). The approach allows researchers to examine the extent to which combinations of two predictor variables relate to an outcome variable, particularly in the case when the discrepancy (difference) between the two predictor variables is a central consideration. We believe this approach has potential for application to a wide variety of research questions. To enhance interest and use of this technique, we provide ideas for future research directions that might benefit from the application of this analytic tool. We also walk through a step-by-step example of how to conduct polynomial regression and response surface analysis and provide all the tools you will need to do the analyses and graph the results (including SPSS syntax, formulas, and a downloadable Excel spreadsheet). Our example involves how discrepancies in perceived supervisor and organizational support relate to affective commitment. Finally, we discuss how this approach is a better, more informative alternative to difference scores and can be applied to the examination of two-way interactions in moderated regression.
KeywordsPolynomial regression Response surface analysis Two-way interactions Job attitudes Research methods
This research was supported, in part, by funds from the University of North Carolina at Charlotte.
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