Factorial validity is often assessed using confirmatory factor analysis. Model fit is commonly evaluated using the cutoff values for the fit indices proposed by Hu and Bentler (1999). There is a body of research showing that those cutoff values cannot be generalized. Model fit does not only depend on the severity of misspecification, but also on nuisance parameters, which are independent of the misspecification. Using a simulation study, we demonstrate their influence on measures of model fit. We specified a severe misspecification, omitting a second factor, which signifies factorial invalidity. Measures of model fit showed only small misfit because nuisance parameters, magnitude of factor loadings and a balanced/imbalanced number of indicators per factor, also influenced the degree of misfit. Drawing from our results, we discuss challenges in the assessment of factorial validity.

中文翻译：

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该度量真的是一维的吗？

析因效度通常使用验证性因子分析进行评估。模型拟合通常使用Hu和Bentler（1999）提出的拟合指数的临界值进行评估。有大量研究表明，这些临界值不能一概而论。模型拟合不仅取决于错误指定的严重程度，还取决于与错误指定无关的令人讨厌的参数。通过仿真研究，我们证明了它们对模型拟合度量的影响。我们指定了严重的错误指定，省略了第二个因素，这表示阶乘无效。模型拟合的量度仅显示出很小的失配，因为令人讨厌的参数，因子负载的大小以及每个因子的平衡/不平衡数量的指标也影响了失配的程度。从我们的结果中