Wiedermann Wolfgang, von Eye Alexander
Unit of Quantitative Methods, Department of Psychology, University of Vienna.
Department of Psychology, Michigan State University.
Psychol Methods. 2015 Jun;20(2):221-44. doi: 10.1037/met0000027. Epub 2015 Mar 9.
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.
社会科学中收集的数据很少呈正态分布。通常用于检验中介假设的线性回归方法所考虑的矩不高于二阶。最近讨论的方向依赖方法确实考虑了更高阶的矩。在回顾了常用的中介分析方法后，本文表明这些方法不允许人们对相互竞争的中介模型做出决策，即考虑因果反向流动的模型。然后，引入了方向依赖方法，该方法允许人们评估效应方向的假设，并将其应用扩展到中介分析。提出并讨论了关于效应方向的统计推断的显著性检验。给出了在各种数据场景下测试性能的蒙特卡罗模拟结果。给出了一个关于亲密伴侣暴力研究的实证例子。最后，讨论了这些方法可能存在的局限性，探讨了关于观察到的偏度来源的隐含假设问题，并将新方法嵌入到更大的因果推断框架中。
