Estimation of Nonlinear Models in the Presence of Measurement Error

Abstract

Techniques used in decision sciences and business research to estimate interactions between latent variables are limited in controlling for measurement error. This article uses a latent structure modeling approach that substantially controls for measurement error in nonlinear relationships. The results of this technique are compared to the results obtained applying hierarchical regression analysis and the impact of measurement error is assessed. The paper provides a unique assessment of the validity of the multi‐attribute attitude model. The validity of the multiplicative rule in the model is supported. Copyright © 1990, Wiley Blackwell. All rights reserved