Estimation of Nonlinear Models in the Presence of Measurement Error*
提出一种潜结构建模方法，能有效控制非线性关系中的测量误差，并与层级回归分析比较，评估了多属性态度模型中乘法规则的有效性。
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.