Lower level mediation in multilevel models
Lower level mediation in multilevel models
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DOI：
10.1037/1082-989x.8.2.115
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发表时间：
2003-06-01
影响因子：
7
通讯作者：
Bolger, N
中科院分区：
文献类型：
--
作者：
Kenny, DA;Korchmaros, JD;Bolger, N
多级模型越来越多地用于估计分层和重复测量数据的模型。作者讨论了一个模型，其中较低级别存在中介，并且中介链接在较高级别单元之间随机变化。一个重复测量的例子是这样一种情况，一个人的日常压力会影响他或她的应对努力，从而影响他或她的情绪，并且这两个联系在不同人之间随机变化。如果较低级别存在中介，并且中介链接在较高级别单元之间随机变化，则必须修改间接效应及其标准误差的公式，以包括随机效应之间的协方差。由于没有标准方法可以估计这样的模型，因此作者开发了一种用真实数据和模拟数据进行说明的临时方法。讨论了该方法的局限性和理想方法的特征。
Multilevel models are increasingly used to estimate models for hierarchical and repeated measures data. The authors discuss a model in which there is mediation at the lower level and the mediational links vary randomly across upper level units. One repeated measures example is a case in which a person's daily stressors affect his or her coping efforts, which affect his or her mood, and both links vary randomly across persons. Where there is mediation at the lower level and the mediational links vary randomly across upper level units, the formulas for the indirect effect and its standard error must be modified to include the covariance between the random effects. Because no standard method can estimate such a model, the authors developed an ad hoc method that is illustrated with real and simulated data. Limitations of this method and characteristics of an ideal method are discussed.