Division of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ 85724, USA.
J Eval Clin Pract. 2013 Feb;19(1):214-22. doi: 10.1111/j.1365-2753.2011.01757.x. Epub 2011 Aug 23.
Marginal structural models were developed to account for a so-called time-dependent confounder and to estimate the presumed effect of 'treatment regime' (treatment over time). We present a set of causal axioms, according to which the problem of time-dependent confounding does not exist, and 'treatment regime' affects nothing. Per our axiomatization, marginal structural models do not introduce a new idea of deconfounding, but simply estimate a weighted average of effects. Whenever a weighted average and the weighting scheme can both be rationalized, the models are acceptable. Whenever a weighted average does not estimate an effect (e.g. important effect modification is ignored), or the weights are senseless - the models should not be fit.
边缘结构模型被开发出来以解释所谓的时依混杂因素，并估计“治疗方案”（随时间的治疗）的假定效果。我们提出了一组因果公理，根据这些公理，时依混杂问题并不存在，而且“治疗方案”没有任何影响。根据我们的公理体系，边缘结构模型并没有引入一种新的去混杂思想，而只是估计了效应的加权平均值。只要加权平均值和加权方案都可以合理化，那么这些模型就是可以接受的。只要加权平均值不能估计效应（例如忽略了重要的效应修饰），或者权重没有意义，那么这些模型就不应该拟合。
