Measurement invariance is assessed in the factor analytic framework by testing differences in model fit of a sequential series of models; however, the statistical significance of these differences is influenced by many factors, including sample size. Effect sizes are independent of sample size and can be used to determine the magnitude and practical importance of an effect. We developed four new effect size measures of measurement non-invariance for continuous outcomes. To test the properties of these effect sizes and of two existing effect sizes of non-invariance, we conducted a simulation study. We varied group sample sizes, location of the latent distributions, magnitude of non-invariance and type of non-invariance (e.g., metric invariance). Three of the effect sizes were unbiased in all conditions and all six were consistent. Recommendations for their use and future directions are discussed.

中文翻译：

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对连续结果的测量非不变性的六个效应量度量的评估

在因子分析框架中，通过测试一系列模型的模型拟合差异来评估测量不变性；然而，这些差异的统计显着性受到许多因素的影响，包括样本量。效应量与样本量无关，可用于确定效应的大小和实际重要性。我们为连续结果开发了四种新的测量非不变性的效应量度量。为了测试这些效应量和两个现有的非不变性效应量的特性，我们进行了模拟研究。我们改变了组样本大小、潜在分布的位置、非不变性的大小和非不变性的类型（例如，度量不变性）。其中三个效应大小在所有条件下都是无偏的，并且所有六个都是一致的。