Quantifying Change Over Time: Interpreting Time-varying Effects In Duration Analyses
Quantifying Change Over Time: Interpreting Time-varying Effects In Duration Analyses
复制标题
量化随时间的变化：解释持续时间分析中随时间变化的影响
DOI：
10.1017/pan.2017.35
复制
发表时间：
2018
影响因子：
5.4
通讯作者：
C. Ruhe
中科院分区：
文献类型：
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作者：
C. Ruhe
政治科学中的持续时间分析通常通过与分析时间的相互作用来模拟非比例风险。为了便于解释，方法学家提出了可视化时变系数或风险比的方法。虽然这些技术是有用的初始后估计步骤，但我认为它们不足以识别时变效应的总体影响，并且当系数改变其符号时可能导致错误的推断。我展示了即使系数符号的显著变化也不意味着整体效应随着时间的推移而逆转。在这种情况下，为了能够正确地解释时变效应，研究人员应该用幸存者函数来可视化他们的结果。我概述了如何为具有时变效应的模型计算幸存者函数，并利用调解对国家间冲突的时变效应的突出发现，论证了这种微妙解释的必要性。使用所提出的可视化方法对数据进行的再分析表明，早期中介研究的结论具有误导性。这个例子强调了幸存者函数是如何澄清事件历史模型中时变系数固有的模糊性的重要工具。
Duration analyses in political science often model nonproportional hazards through interactions with analysis time. To facilitate their interpretation, methodologists have proposed methods to visualize time-varying coefficients or hazard ratios. While these techniques are a useful, initial postestimation step, I argue that they are insufficient to identify the overall impact of a time-varying effect and may lead to faulty inference when a coefficient changes its sign. I show how even significant changes of a coefficient’s sign do not imply that the overall effect is reversed over time. In order to enable a correct interpretation of time-varying effects in this context, researchers should visualize their results with survivor functions. I outline how survivor functions are calculated for models with time-varying effects and demonstrate the need for such a nuanced interpretation using the prominent finding of a time-varying effect of mediation on interstate conflict. The reanalysis of the data using the proposed visualization methods indicates that the conclusions of earlier mediation research are misleading. The example highlights how survivor functions are an essential tool to clarify the ambiguity inherent in time-varying coefficients in event history models.