Some scholars have argued that the multiplicative form of EV models is not as optimal as additive models in the prediction of attitudes (Trafimow & Finlay, 2002). While we acknowledge that there are many types of models (theoretical and atheoretical) that can be used to predict attitudes from beliefs, evaluations, and importance, this paper focuses specifically on potential contributions made by importance measures to the most frequently used EV models, where attitude is assumed to be a function of the sum of Beliefs × Evaluations.
The Predictive Benefits of Importance: Do Issue Importance Ratings Improve the Prediction of Political Attitudes?
Article first published online: 31 JUL 2006
Journal of Applied Social Psychology
Volume 35, Issue 3, pages 487–507, March 2005
How to Cite
Kenski, K. and Fishbein, M. (2005), The Predictive Benefits of Importance: Do Issue Importance Ratings Improve the Prediction of Political Attitudes?. Journal of Applied Social Psychology, 35: 487–507. doi: 10.1111/j.1559-1816.2005.tb02132.x
- Issue published online: 31 JUL 2006
- Article first published online: 31 JUL 2006
Using data collected in Arizona during the 2000 Presidential election, this study explores whether expectancy value (EV) models predicting attitudes toward candidates and toward voting for candidates can be improved by incorporating measures of issue importance. More specifically, attitudes toward candidates were predicted from beliefs about the candidates’ stands on 8 issues, and attitudes toward voting for the candidates were predicted from beliefs that voting for a candidate would lead to the implementation of the 8 issue positions. Ratings of the importance of the 8 issues were used to develop several different EV models. The results of our study indicate that importance ratings do not add much to the EV model's prediction of attitudes.