Direction of effects in mediation analysis.

Direction of effects in mediation analysis.
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中介分析中的效应方向。

DOI:
10.1037/met0000027
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发表时间:
2015
影响因子:
7
通讯作者:
A. von Eye
A. von Eye
中科院分区:
心理学1区
文献类型:
--
作者:
W. Wiedermann;A. von Eye

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在社会科学中收集的数据很少是正态分布的。通常用于检验中介假设的线性回归方法考虑不高于二阶的矩。最近讨论的方向依赖性的方法考虑更高的时刻。在回顾了常用的调解分析方法后,本文表明,这些方法不允许人们对竞争性调解模型做出决定,即考虑因果关系反向流动的模型。然后,方向的依赖方法,它允许一个评估假设的影响方向,并将其应用扩展到中介分析。统计推断的影响方向的显着性检验提出和讨论。各种数据情况下的测试性能的蒙特-卡罗模拟的结果。文中给出了一个关于亲密伴侣暴力行为研究的实证例子。最后,这些方法可能存在的局限性进行了讨论,隐式假设的问题有关的起源观察偏度进行了讨论,并嵌入到更大的框架内的因果推理的新方法。
Data collected in the social sciences are rarely normally distributed. The linear regression methods that are usually employed to test mediation hypotheses consider moments no higher than second order. Recently discussed methods of direction dependence do consider higher moments. After a review of commonly used methods for mediation analysis, the present article demonstrates that these methods do not allow one to make decisions about competing mediation models, that is, models in which the reverse flow of causality is considered. Then, direction of dependence methodology is introduced which allows one to evaluate hypotheses of direction of effects, and extend its application to mediation analysis. Significance tests for statistical inference on direction of effects are proposed and discussed. Results of a Monte-Carlo simulation of the performance of the tests under various data scenarios are presented. An empirical example from research on intimate partner violence is given. Finally, possible limitations of these methods are addressed, issues of implicit assumptions concerning the origin of observed skewness are discussed, and the new methodology is embedded into the larger framework of causal inference.
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