On Flexible Inverse Probability of Treatment and Intensity Weighting: Informative Censoring, Variable Inclusion, and Weight Trimming
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灵活逆处理概率与逆强度加权：信息性删失、变量纳入和权重截尾
- 研究问题
- 在观测时间不规则且可能依赖结局的纵向数据中，联合加权方法对信息性删失、观测强度模型的变量选择和极端权重有多敏感？
- 方法与思路
- 作者研究同时调整非随机处理分配与信息性观测过程的灵活加权方法，考察删失假设违反、逆强度模型变量纳入及权重截尾的影响。
- 材料陈述的贡献
- 摘要称，方法及既有扩展对信息性删失存在脆弱性，观测与结局过程的混杂变量应纳入强度模型；处理机制驱动极端权重时应考虑截尾。
- 阅读关注点
- 应核对删失与观测过程的区分、处理和观测权重如何组合、变量纳入依据，以及截尾阈值如何影响偏差、方差和目标效应。
- 阅读边界
- 依据所给 arXiv 预印本摘要，不能确认同行评审或期刊接收。摘要未说明完整识别假设和截尾规则，相关建议的适用范围仍须查阅全文。
原文摘要
Many observational studies feature irregular longitudinal data, where the observation times are not common across individuals in the study. Further, the observation times may be related to the longitudinal outcome. In this setting, failing to account for the informative observation process may result in biased causal estimates. This can be coupled with other sources of bias, including non-randomized treatment assignments and informative censoring. This paper provides an overview of a flexible weighting method used to adjust for informative observation processes and non-randomized treatment assignments. We investigate the sensitivity of the flexible weighting method to violations of the noninformative censoring assumption, examine variable selection for the observation process weighting model, known as inverse intensity weighting, and look at the impacts of weight trimming for the flexible weighting model. We show that the flexible weighting method is sensitive to violations of the noninformative censoring assumption and show that a previously proposed extension fails under such violations. We also show that variables confounding the observation and outcome processes should always be included in the observation intensity model. Finally, we show that weight trimming should be applied in the flexible weighting model when the treatment assignment process is highly informative and driving the extreme weights. We conclude with an application of the methodology to a real data set to examine the impacts of household water sources on malaria diagnoses.