Fairchild Amanda J, Abara Winston E, Gottschall Amanda C, Tein Jenn-Yun, Prinz Ronald J
University of South Carolina, Columbia, SC, USA
University of South Carolina, Columbia, SC, USA.
Eval Health Prof. 2015 Sep;38(3):315-42. doi: 10.1177/0163278713512124. Epub 2013 Dec 2.
The purpose of this article is to introduce and describe a statistical model that researchers can use to evaluate underlying mechanisms of behavioral onset and other event occurrence outcomes. Specifically, the article develops a framework for estimating mediation effects with outcomes measured in discrete-time epochs by integrating the statistical mediation model with discrete-time survival analysis. The methodology has the potential to help strengthen health research by targeting prevention and intervention work more effectively as well as by improving our understanding of discretized periods of risk. The model is applied to an existing longitudinal data set to demonstrate its use, and programming code is provided to facilitate its implementation.
本文的目的是介绍和描述一种统计模型，研究人员可以使用该模型来评估行为发作和其他事件发生结果的潜在机制。具体而言，本文通过将统计中介模型与离散时间生存分析相结合，开发了一个用于估计离散时间阶段测量结果的中介效应的框架。该方法有潜力通过更有效地针对预防和干预工作以及通过增进我们对离散风险期的理解来帮助加强健康研究。该模型应用于现有的纵向数据集以展示其用途，并提供了编程代码以促进其实施。
