A Multimethod SEM Framework for Analyzing Models with Latent Variables

Joseph F. Hair

doi:10.1080/08911762.2026.2638909

2026-03-10

Joseph F. Hair

Pratyush Nidhi Sharma *

Wynne W. Chin

Marko Sarstedt *

Christian M. Ringle *

DOI：10.1080/08911762.2026.2638909

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摘要

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结构方程模型（SEM）被广泛用于估计潜变量及其指标变量之间的关系。尽管存在不同方法，但研究人员往往依赖单一估计传统——基于因子或基于复合的方法——尽管它们具有不同的假设、优势和局限性。这种做法限制了结构模型的严格评估，特别是对于需要同时进行解释性和预测性评估的理论。本文介绍了一个多方法SEM框架，该框架将基于因子和基于复合的估计器应用于同一模型，以评估在不同概念和统计假设下结构路径的稳健性。我们概述了实施多方法估计以及评估结果收敛与发散的工作流程。这一多方法SEM框架将关注点从方法忠诚度转向模型的实证表现，从而提升理论推断、预测评估以及基于SEM结论的整体可信度。

Keyword:

Composite-based SEM

explanatory power

factor-based SEM

multimethod SEM

predictive power

structural equation modeling (SEM)

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Journal of Global Marketing

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