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Asian researchers should be more critical: The example of testing mediators using time-lagged data

机译:亚洲研究人员应该更具批判性:使用时滞数据测试调解员的示例

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In the past decade, there has been call for Asian researchers to be more confident and not limit themselves to follow only the footsteps of Western studies. In this paper, we follow up the discussion in Western literature about the importance of testing mediators with longitudinal data. The prevailing way of testing mediation is the use of time-lagged models. That is, the predictor or mediator is collected at prior time points than the outcome variable. We believe this is not sufficient. Instead, cross-lagged models, which measure all three types of variables at different time points, are necessary for testing mediation. Unfortunately, Asian researchers have again followed the footsteps of the suboptimal practice of time-lagged models. Using computer simulation data and a real-life dataset collected in China, we show that erroneous conclusions may be drawn even when the predictor, the mediator, and outcome variables are measured at different time waves under the time-lagged model. We propose a more appropriate procedure to use the cross-lagged model to test the exact causal ordering among the predictor, the mediator, and the outcome variable.
机译:在过去的十年中,一直呼吁亚洲研究人员更加自信,而不是仅仅追随西方研究的脚步。在本文中,我们跟进了西方文献中有关使用纵向数据测试中介者的重要性的讨论。测试调解的主要方法是使用时滞模型。也就是说,在比结果变量更早的时间点收集预测变量或中介变量。我们认为这还不够。相反,交叉中介模型对于测试中介是必需的,该模型在不同时间点测量所有三种类型的变量。不幸的是,亚洲研究人员再次追随了时滞模型欠佳实践的脚步。使用计算机模拟数据和在中国收集的现实生活数据集,我们表明,即使在时滞模型下以不同的时间波测量了预测变量,中介变量和结果变量,也可能得出错误的结论。我们提出了一个更合适的程序来使用交叉滞后模型来测试预测变量,中介变量和结果变量之间的确切因果顺序。

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