In February 2010, a massive earthquake struck Chile, causing devastation in certain parts of the country, affecting other areas, and leaving territories untouched. 2 months after the earthquake, Chile's Ministry of Social Development reinterviewed a representative subsample of its National Socioeconomic Characterization Survey, which had been completed 2 months before the earthquake, thereby creating a prospective longitudinal survey with detailed information of the same individuals before and after the earthquake. We use a new weighting method for non‐experimental studies with multivalued treatments to estimate the effect of levels of exposure to the earthquake on post‐traumatic stress. Unlike common weighting approaches for multivalued treatments, this new method does not require explicit modelling of the generalized propensity score and instead focuses on directly balancing the covariates across the multivalued treatments with weights that have minimum variance. As a result, the weighting estimator is stable and approximately unbiased. Furthermore, the weights are constrained to avoid model extrapolation. We illustrate this new method in a simulation study, with both categorical and continuous treatments. The results show that directly targeting balance instead of explicitly modelling the treatment assignment probabilities tends to provide the best results in terms of bias and root‐mean‐square error. Using this method, we estimate the effect of the intensity of the earthquake on post‐traumatic stress. We implement this method in the new package msbw for R.

中文翻译：

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在具有多值治疗的非实验研究中直接和稳定地调整体重：分析地震对创伤后压力的影响

2010年2月，智利发生了一场大地震，在该国某些地区造成了破坏，并影响了其他地区，并保持了领土的原貌。地震发生2个月后，智利社会发展部对国家社会经济特征调查的代表性子样本进行了重新访谈，该调查已在地震发生前2个月完成，从而创建了一项前瞻性纵向调查，其中包含地震前后同一个人的详细信息。 。对于具有多值处理的非实验研究，我们使用一种新的加权方法来估计地震暴露水平对创伤后压力的影响。与多值治疗的常见加权方法不同，这种新方法不需要对广义倾向得分进行显式建模，而是着重于通过具有最小方差的权重直接平衡多值处理之间的协变量。结果，加权估计器是稳定的并且近似无偏。此外，权重受到约束以避免模型外推。我们在模拟研究中说明了这种新方法，包括分类处理和连续处理。结果表明，直接针对平衡而不是对治疗分配概率进行显式建模往往会在偏差和均方根误差方面提供最佳结果。使用这种方法，我们估计了地震烈度对创伤后压力的影响。我们在R的新程序包msbw中实现了此方法。