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稳健模型检验研究 — 稳健SEM与结构模型评估

稳健模型检验研究在应用结构模型或路径模型于数据时,会明确考虑多元正态性及其他分布假设的违反情况。它不丢弃非正态数据或强制进行变量变换,而是采用修正后的估计量——最显著的是 Satorra-Bentler 缩放卡方(scaled chi-square)和 Yuan-Bentler 稳健标准误(robust standard errors)——即使在经典最大似然(maximum likelihood)假设被打破时,也能产生可信的拟合指数(fit indices)和参数估计值。

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来源

  1. Satorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Sage. link
  2. Yuan, K.-H., & Bentler, P. M. (1998). Robust mean and covariance structure analysis. British Journal of Mathematical and Statistical Psychology, 51(1), 63–88. DOI: 10.1111/j.2044-8317.1998.tb00667.x

如何引用本页

ScholarGate. (2026, June 3). Robust Model Testing Research Design. ScholarGate. https://scholargate.app/zh/research-design/robust-model-testing-research

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

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ScholarGateRobust Model Testing Research (Robust Model Testing Research Design). 于 2026-06-15 检索自 https://scholargate.app/zh/research-design/robust-model-testing-research · 数据集: https://doi.org/10.5281/zenodo.20539026