Structural Nested Cumulative Failure Time Models to Estimate the Effects of Interventions
用于估计干预效应的结构嵌套累积失败时间模型
In the presence of time-varying confounders affected by prior treatment, standard statistical methods for failure time analysis may be biased. Methods that correctly adjust for this type of covariate include the parametric g-formula, inverse probability weighted estimation of marginal structural Cox proportional hazards models, and g-estimation of structural nested accelerated failure time models. In this article, we propose a novel method to estimate the causal effect of a…