Suppressor Variables in Social Work Research: Ways to Identify in Multiple Regression Models

By Shanta Pandey, William Elliott. Journal of the Society for Social Work and Research, 2010

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Suppressor Variables: The Difference Between ‘is’ Versus ‘Acting As’ (2014, background): “…designs, how they are related to other so-called third variable effects, an application with real data that illustrates results and interpretations depending on which of three proposed suppressor design or suppression analysis strategies are taken, and recommendations for teaching and research.”
Identifying the Limitation of Stepwise Selection for Variable Selection in Regression Analysis (2015, background): “Including such a variable will eliminate the danger of rejecting a true hypothesis as false (Shanta & Williams, 2010).”
What residualizing predictors in regression analyses does (and what it does not do) (2014, background): “Put another way, the predictor whose sign has changed accounts for (or suppresses) a portion of the variance in the other predictor that is unrelated to the DV (Pandey & Elliott, 2010).”
Success, Failure, and Entrepreneurial Reentry: An Experimental Assessment of the Veracity of Self–Efficacy and Prospect Theory (2017, result): “These results indicated that the relationship between performance and postexperiment intention was “blurred” because of outcome irrelevant variance in the predictor (performance in our case) (Pandey & Elliott, 2010, p.36).”