The Chronicler's Web (TCW)

by DAN CALLOWAY
Published 2 August 2010

WEAVERVILLE, NC – For the purposes of this discussion, I will explore the direct effect of education on political attitudes, the indirect effect of income on political attitudes, and defend my consideration of one over the other. For this article, we will assume that education has been identified as the predictor variable and political attitude is viewed as the criterion variable. The effect of income on the criterion variable is seen as an indirect effect attributed to income known as the suppressor variable rather than a mediator variable. Conger and Jackson (1972) indicates that there is considerable disagreement on what constitutes a suppressor variable and that there has been little research in the manner of relating suppressor variables to the more well known partial correlation and moderator variable. Confusion surrounding the precise definition of a suppressor variable stems from a reinterpretation and relaxing of the Horst (1941) definition, which contained its mode of operation and its mathematical foundation. The classical definition of a suppressor variable provided by Conger and Jackson is a variable “wholly uncorrelated with the criterion, but which, by virtue of a correlation with the predictor, improves the prediction of the criterion” (p. 581). The paradoxical quality of the suppressor variable is that it is possible to increase the prediction of the criterion by utilizing a variable that has a negligible correlation with the criterion, provided that it does correlate with another variable that correlates well with the criterion. To further illustrate this concept, one need examine the prediction in the success of WWII pilot training programs as relayed in Horst (1966, p. 355), in which a battery of tests were given to pilots to evaluate their mechanical, numerical, spatial, and verbal abilities. Noteworthy here is that the first three predictor variables had positive correlations to the criterion variable but the last, verbal ability, had virtually no correlation to the criterion, yet had high correlations with each of the first three predictor variables.

Bobo and Licari (1989) sought to examine the positive relationship between education and political tolerance. The authors identified that one of the more prominent explanations for the positive relationship between education and political tolerance is the enhanced cognitive sophistication on the part of the learner brought about by the additional years of higher education. Through their secondary research into the direct measure of cognitive sophistication as a predictor of political tolerance (a more quantifiable criterion variable), they discovered that cognitive sophistication is the mediating variable or mediating link between education and political tolerance. What Bobo and Licari were able to show was that cognitive sophistication largely mediates the relationship between education and political tolerance above and beyond the moderating variables of age, gender, race, religion, urbanicity, and ideology.

Therefore, I would choose to examine the direct effect of the predictor variable, education, on political attitudes (or tolerance) by first determining whether there is a direct correlation between the suppressor variable, income, and the predictor variable, education. As pointed out in Lubin (1957)⁠ if a high correlation can be shown between the suppressor variable and the predictor variable, then the multiple correlation could be increased significantly. Thus, by demonstrating that a positive correlation between education and income exists, one could then significantly increase the likelihood that there is a positive correlation between education and political tolerance through multiple correlation. The study conducted by Bobo and Licari (1989) helps to reinforce this direct relationship between the predictor variable and the criterion for this discussion.

Bobo, L., & Licari, F. (1989). Education and political tolerance: Testing the effects of cognitive sophistication and target group effect. Public Opinion Quarterly, 53(3), 285-308.

Conger, A., & Jackson, D. (1972). Suppressor variables, prediction, and the interpretation of psychological relationships. Educational and Psychological Measurement, 32(3), 579-599.

Horst, P. (1941). The prediction of personal adjustment. New York, NY.

Horst, P. (1966). Psychological measurement and prediction. Belmont, California: Wadsworth.

Lubin, A. (1957). Some formulae for use with suppressor variables. Educational and Psychological Measurement, 17(2), 286-297.