Abstract In this paper we present a continuous extension for longitudinal analysis settings of the recently proposed Covariate Balancing Propensity Score (CBPS) methodology. While extensions of the CBPS methodology to both marginal structural models and general treatment regimes have been proposed, these extensions have been kept separately. We propose to bring them together using the generalized method of moments to estimate inverse probability weights such that after weighting the association between time-varying covariates and the treatment is minimized. A simulation analysis confirms the correlation-breaking performance of the proposed technique. As an empirical application we look at the impact the gradual roll-out of Seguro Popular, a universal health insurance program, has had on the resources available for the provision of healthcare services in Mexico.

中文翻译：

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时变连续干预的协变量平衡逆概率权重

摘要 在本文中，我们提出了最近提出的协变量平衡倾向评分 (CBPS) 方法的纵向分析设置的连续扩展。虽然已经提议将 CBPS 方法扩展到边缘结构模型和一般治疗方案，但这些扩展已单独保留。我们建议使用广义矩方法将它们组合在一起以估计逆概率权重，以便在对时变协变量与治疗之间的关联进行加权后最小化。仿真分析证实了所提出技术的相关性破坏性能。作为一项实证应用，我们考察了全民健康保险计划 Seguro Popular 逐步推出的影响，