Naimi Ashley I, Cole Stephen R, Kennedy Edward H
Department of Epidemiology, University of Pittsburgh.
Department of Epidemiology, University of North Carolina at Chapel Hill and.
Int J Epidemiol. 2017 Apr 1;46(2):756-762. doi: 10.1093/ije/dyw323.
Robins' generalized methods (g methods) provide consistent estimates of contrasts (e.g. differences, ratios) of potential outcomes under a less restrictive set of identification conditions than do standard regression methods (e.g. linear, logistic, Cox regression). Uptake of g methods by epidemiologists has been hampered by limitations in understanding both conceptual and technical details. We present a simple worked example that illustrates basic concepts, while minimizing technical complications.
罗宾斯广义方法（g方法）在比标准回归方法（如线性回归、逻辑回归、Cox回归）限制更少的识别条件下，提供了潜在结果对比（如差异、比率）的一致性估计。流行病学家对g方法的采用受到了在理解概念和技术细节方面的限制。我们给出一个简单的实例，以说明基本概念，同时尽量减少技术复杂性。
