Jasti Srichand, Dudley William N, Goldwater Eva
Emma Eccles Jones Nursing Research Center, University of Utah College of Nursing, Salt Lake City, UT 84112, USA.
Nurs Res. 2008 Mar-Apr;57(2):118-22. doi: 10.1097/01.NNR.0000313479.55002.74.
Statistical mediation is an important tool in behavioral health sciences, but it has been confined primarily to continuous variables. As prevention studies become increasingly common, more often the mediator or outcome is binary. Recent work by D. P. MacKinnon and J. H. Dwyer (1993) has explicated the steps necessary to estimate models for mediation when the mediator or the outcome is binary.
To report the release of a set of SAS macros used to implement the statistical analyses required to analyze data with binary and continuous-level data.
A brief introduction to the methodology of mediation analysis in the presence of a binary outcome, mediator, or both is provided. The macros are tested on a sample of 84 participants who were experiencing pain. It is hypothesized that the relationship between pain and fatigue is mediated by sleep disturbance.
The relationship between pain and fatigue was mediated by the presence of sleep disturbances, and the amount of mediation was 23.34%.
The SAS macros are available for download without charge from the second author's Web site. Instructions are provided in an included technical manual.
统计中介是行为健康科学中的一项重要工具，但它主要局限于连续变量。随着预防研究变得越来越普遍，中介变量或结果变量更常为二元变量。D. P. 麦金农和J. H. 德怀尔（1993年）最近的研究阐述了当中介变量或结果变量为二元变量时估计中介模型所需的步骤。
报告发布一组SAS宏程序，用于对二元和连续水平数据进行分析时实施所需的统计分析。
简要介绍存在二元结果变量、中介变量或两者皆有时的中介分析方法。这些宏程序在84名正在经历疼痛的参与者样本上进行了测试。假设疼痛与疲劳之间的关系由睡眠障碍介导。
疼痛与疲劳之间的关系由睡眠障碍介导，中介效应量为23.34%。
可从第二作者的网站免费下载这些SAS宏程序。随附的技术手册中提供了使用说明。
