[Overview on the generalized propensity scoring estimator for continuous treatment].

Among kinds of methods for causal inference in observational studies, the propensity score (PS) method to control measured confounding is more widely used. PS method usually consists of two critical steps: first, estimating the propensity score, followed by calculating the causal parameters of interest by regression, weighting, matching, and stratification. Unlike the traditional dichotomous treatment, the generalized propensity scoring estimator used for continuous treatment has been proposed in recent years. Many methods have been developed to estimate the generalized propensity score or even estimate the balancing weight directly. This paper introduces the existing estimators from both the model-based and balance-based perspectives.在观察性研究中进行因果推断的众多方法中，用于控制已测量混杂的倾向性评分方法应用越来越广泛。该类方法主要分为两步：首先估计倾向性评分，然后采取回归、加权、匹配和分层等手段进一步估计感兴趣的因果参数。不同于传统的二分类处理情况，近年来针对连续型处理因素的广义倾向性评分方法被提出。目前已发展出了许多估计广义倾向性评分和直接估计均衡权重的方法，本文将从基于模型和基于均衡性两个角度出发对现有方法进行介绍。.