Measurement Models for Reasoned Action Theory

Abstract

Quantitative researchers distinguish between causal and effect indicators. What are the analytic problems when both types of measures are present in a quantitative reasoned action analysis? To answer this question, we use data from a longitudinal study to estimate the association between two constructs central to reasoned action theory: behavioral beliefs and attitudes toward the behavior. The belief items are causal indicators that define a latent variable index while the attitude items are effect indicators that reflect the operation of a latent variable scale. We identify the issues when effect and causal indicators are present in a single analysis and conclude that both types of indicators can be incorporated in the analysis of data based on the reasoned action approach.

Figure 1

The Generic Measurement Model for the Attitude Component of the Integrative Model

Figure 2. Behavioral Belief Items Treated as a Two-Factor Effect Indicator Measurement Model

Notes: N = 460. All are standardized coefficients. All coefficients are discernable from zero. Goodness of Fit: χ² = 596, df = 28, p < .05, Tucker-Lewis Index = .69, RMSEA = .21. Item list is: #1: Make me feel as though someone had taken advantage of me. #2: Make me feel good about myself. #3: Hurt my relationship with my partner. #4: Increase the quality of my relationship with my partner. #5: Increase feeling of intimacy between me and my partner. #6: Give me pleasure. #7: Make my parents mad. #8: Please my partner. #9: Get me or my partner pregnant. #10: Gain the respect of my friends. #11: Give me a STD or HIV/AIDS. #12: Make my friends think badly of me.