Visualizing interaction effects: a proposal for presentation and interpretation
Visualizing interaction effects: a proposal for presentation and interpretation
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DOI：
10.1016/j.jclinepi.2012.02.013
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发表时间：
2012-08-01
影响因子：
7.2
通讯作者：
Kronenberg, Florian
中科院分区：
文献类型：
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作者：
Lamina, Claudia;Sturm, Gisela;Kronenberg, Florian
目的：交互作用项通常包含在回归模型中，以测试一个变量对结果的影响是否被另一个变量所修改。然而，对这些模型的解释往往并不清楚。我们提出了几个图形演示和相应的统计测试减轻解释interaction effects.Study设计和设置：我们实现了功能的统计程序R，可用于在线性，逻辑和考克斯比例风险模型的相互作用。生存数据进行了模拟，以显示我们提出的图形可视化methods.Results的功能：相互作用项的相互修改效果是掌握我们提出的数字和方法：两个连续变量的组合效果是由一个二维表面模仿3D图。此外，显着性区域计算的两个变量中涉及的相互作用项，回答的问题，其中一个变量的值的其他变量的效果显着不同，从zero.Conclusion：我们提出了几个图形可视化的方法，以减轻解释的相互作用的影响，使任意分类不必要的。通过这些方法，研究人员和临床医生都配备了必要的信息，以评估相互作用的临床相关性和影响。(C)2012 Elsevier Inc. All rights reserved.
Objective: Interaction terms are often included in regression models to test whether the impact of one variable on the outcome is modified by another variable. However, the interpretation of these models is often not clear. We propose several graphical presentations and corresponding statistical tests alleviating the interpretation of interaction effects.Study Design and Setting: We implemented functions in the statistical program R that can be used on interaction terms in linear, logistic, and Cox Proportional Hazards models. Survival data were simulated to show the functionalities of our proposed graphical visualization methods.Results: The mutual modifying effect of the interaction term is grasped by our presented figures and methods: the combined effect of both continuous variables is shown by a two-dimensional surface mimicking a 3D-Plot. Furthermore, significance regions were calculated for the two variables involved in the interaction term, answering the question for which values of one variable the effect of the other variable significantly differs from zero and vice versa.Conclusion: We propose several graphical visualization methods to ease the interpretation of interaction effects making arbitrary categorizations unnecessary. With these approaches, researchers and clinicians are equipped with the necessary information to assess the clinical relevance and implications of interaction effects. (C) 2012 Elsevier Inc. All rights reserved.