Measurement Models for Reasoned Action Theory

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, the authors 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. The authors identify the issues when effect and causal indicators are present in a single analysis and conclude that both types of indicators can be incorporated into analyses of data based on the reasoned action approach.