Generalized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model evaluation, including the goodness-of-fit index (GFI) and the standardized root mean square residual (SRMR). While these indexes have a solid standing in factor-based structural equation modeling, nothing is known about their performance in GSCA. Addressing this limitation, we present a simulation study’s results, which confirm that both GFI and SRMR indexes distinguish effectively between correct and misspecified models. Based on our findings, we propose rules-of-thumb cutoff criteria for each index in different sample sizes, which researchers could use to assess model fit in practice.

中文翻译：

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广义结构化零件分析中总体模型拟合指标的临界标准

广义结构化组件分析（GSCA）是基于组件的结构方程建模的一种技术完善的方法，可用于指定和检查观察到的变量及其组件之间的关系。GSCA提供了用于模型评估的总体拟合指标，包括拟合优度指标（GFI）和标准化均方根残差（SRMR）。尽管这些索引在基于因子的结构方程模型中具有坚实的地位，但对其在GSCA中的性能一无所知。针对此限制，我们提供了模拟研究的结果，证实了GFI和SRMR指数可以有效地区分正确和错误指定的模型。根据我们的发现，我们针对不同样本量的每个指数提出了经验法则截止标准，