Abstract Covariance Based – Structural Equation Modelling (CB-SEM) is often used to investigate moderation and latent interaction effects. This study illustrates and compares the application of constrained, unconstrained and orthogonalized CB-SEM approaches to latent variable interaction analysis using AMOS. Although all three techniques provided similar parameter estimates, the orthogonalized approach provided reduced standard errors resulting in identifying a significant latent interaction, suggesting the orthogonalized approach may be better suited for exploratory research. The illustrated example demonstrates three CB-SEM techniques, and the simplicity of the three approaches to test for interaction effects. The three approaches can be comfortably implemented in available software programs. Guidelines and recommendations for the use of the three approaches are identified with a step-wise process of assessing the latent interaction effect in CB-SEM. As far as we are aware this is the first investigation comparing and recommending specific CB-SEM latent variable moderation analysis techniques in marketing research.

中文翻译：

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CB-SEM潜在相互作用：无约束和正交的方法

基于协方差的抽象-结构方程模型（CB-SEM）通常用于研究调节和潜在相互作用的影响。这项研究说明并比较了约束，无约束和正交的CB-SEM方法在使用AMOS进行潜在变量相互作用分析中的应用。尽管所有这三种技术都提供了相似的参数估计，但是正交化方法减少了标准误差，从而导致识别出明显的潜在相互作用，这表明正交化方法可能更适合于探索性研究。所示示例演示了三种CB-SEM技术，以及三种测试相互作用效应的方法的简便性。这三种方法可以在可用的软件程序中轻松实现。通过分步评估CB-SEM中潜在的相互作用效应，确定了使用这三种方法的指南和建议。据我们所知，这是在市场研究中比较和推荐特定CB-SEM潜在变量缓和分析技术的第一个调查。