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ERIC Number: ED407420
Record Type: Non-Journal
Publication Date: 1997-Jan
Pages: 17
Abstractor: N/A
Reference Count: N/A
How Variables Uncorrelated with the Dependent Variable Can Actually Make Excellent Predictors: The Important Suppressor Variable Case.
Woolley, Kristin K.
Many researchers are unfamiliar with suppressor variables and how they operate in multiple regression analyses. This paper describes the role suppressor variables play in a multiple regression model and provides practical examples that explain how they can change research results. A variable that when added as another predictor increases the total correlation coefficient squared (R squared) is a suppressor variable. Suppressor variables measure invalid variance in the predictor measures and serve to suppress this invalid variance. Two practical examples of the effects of suppressor variables are given. One involves the selection of airplane pilots and the other concerns the determination of behaviors that predict a woman's intention to have a Pap test. An appendix presents a classroom demonstration that demonstrates the importance of identifying suppressor variables and how they affect research outcomes. (Contains three figures and nine references.) (SLD)
Publication Type: Reports - Evaluative; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A