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Why generalized structured component analysis is not universally preferable to structural equation modeling

机译:为什么广义结构化组件分析并不普遍优于结构方程模型

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摘要

Generalized structured component analysis has emerged in marketing and psychometric literature as an alternative to structural equation modeling. A recent simulation study recommends that, in most cases, this analysis is preferable to structural equation modeling because it outperforms the latter when the model is misspecified. This article examines the characteristics of generalized structured component analysis and reveals that the surprising previous findings are attributable to an incomplete experimental design and an error incurred during the software implementation of generalized structured component analysis. Simulated data show that generalized structured component analysis provides inconsistent estimates. In some instances, model misspecification can nearly neutralize this inconsistency, but in others it will reinforce the inconsistency. Moreover, generalized structured component analysis is hardly suitable for mediation analysis because it substantially overestimates the direct effect. Thus, generalized structured component analysis cannot be recommended universally over structural equation modeling.
机译:市场营销和心理计量学文献已经出现了通用的结构化成分分析,作为结构方程模型的替代方法。一项最新的仿真研究建议,在大多数情况下,此分析优于结构方程模型,因为当模型指定不正确时,它优于结构方程模型。本文研究了广义结构化组件分析的特征,并揭示了先前令人惊讶的发现是由于实验设计不完整以及在广义结构化组件分析的软件实现过程中发生的错误。模拟数据表明,广义结构化成分分析提供的估计不一致。在某些情况下,模型错误指定几乎可以消除这种不一致,但是在其他情况下,它将加剧这种不一致。此外,广义结构化成分分析几乎不适合进行中介分析,因为它大大高估了直接影响。因此,不能普遍推荐在结构方程模型上进行广义结构化组件分析。

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    Henseler Jörg;

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  • 年度 2012
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