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首页> 外文期刊>Educational and Psychological Measurement >A Note on Testing Mediated Effects in Structural Equation Models: Reconciling Past and Current Research on the Performance of the Test of Joint Significance
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A Note on Testing Mediated Effects in Structural Equation Models: Reconciling Past and Current Research on the Performance of the Test of Joint Significance

机译：关于在结构方程模型中测试中介效应的注释：协调过去和当前对联合意义测试的性能的研究

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Methods to assess the significance of mediated effects in education and the social sciences are well studied and fall into two categories: single sample methods and computer-intensive methods. A popular single sample method to detect the significance of the mediated effect is the test of joint significance, and a popular computer-intensive method to detect the significance of the mediated effect is the bias-corrected bootstrap method. Both these methods are used for testing the significance of mediated effects in structural equation models (SEMs). A recent study by Leth-Steensen and Gallitto 2016 provided evidence that the test of joint significance was more powerful than the bias-corrected bootstrap method for detecting mediated effects in SEMs, which is inconsistent with previous research on the topic. The goal of this article was to investigate this surprising result and describe two issues related to testing the significance of mediated effects in SEMs which explain the inconsistent results regarding the power of the test of joint significance and the bias-corrected bootstrap found by Leth-Steensen and Gallitto 2016. The first issue was that the bias-corrected bootstrap method was conducted incorrectly. The bias-corrected bootstrap was used to estimate the standard error of the mediated effect as opposed to creating confidence intervals. The second issue was that the correlation between the path coefficients of the mediated effect was ignored as an important aspect of testing the significance of the mediated effect in SEMs. The results of the replication study confirmed prior research on testing the significance of mediated effects. That is, the bias-corrected bootstrap method was more powerful than the test of joint significance, and the bias-corrected bootstrap method had elevated Type 1 error rates in some cases. Additional methods for testing the significance of mediated effects in SEMs were considered and limitations and future directions were discussed.
机译：评估介导作用在教育和社会科学中的重要性的方法已得到很好的研究，分为两类：单样本方法和计算机密集型方法。一种检测介导作用的重要性的流行的单样本方法是联合显着性检验，一种检测介导作用的重要性的流行的计算机密集型方法是偏差校正自举法。这两种方法均用于测试结构方程模型（SEM）中介导效应的重要性。 Leth-Steensen和Gallitto的最新研究2016年提供的证据表明，联合显着性检验比用于检测SEM的介导效应的偏置校正自举法更强大，这与之前对该主题的研究不一致。本文的目的是研究这一令人惊讶的结果，并描述两个与测试SEM中介导效应的重要性有关的问题，这两个问题解释了有关联合重要性测试的功效和Leth-Steensen发现的经偏置校正的自举的不一致结果和Gallitto2016。第一个问题是偏差校正自举方法执行不正确。与创建置信区间相反，使用偏差校正的自举法来估计介导效应的标准误差。第二个问题是，介导效应的路径系数之间的相关性被忽略，这是检验SEM中介导效应的重要性的重要方面。复制研究的结果证实了先前关于测试介导作用的重要性的研究。也就是说，偏差校正的自举方法比联合显着性检验更强大，并且偏差校正的自举方法在某些情况下具有提高的Type 1错误率。考虑了测试SEM中介导效应的重要性的其他方法，并讨论了局限性和未来方向。

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