Bayesian inference on average treatment effects in the PreventS trial data in the presence of unmeasured confounding
未测混杂下 PreventS 试验平均处理效应的贝叶斯推断AI 解读 ↓
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未测混杂下 PreventS 试验平均处理效应的贝叶斯推断
- 研究问题
- 在双臂随机试验存在多个相关多值暴露、未测混杂、不依从及缺失数据时，如何估计健康教练干预在不同时间段的平均效果？
- 方法与思路
- 作者提出贝叶斯因果建模框架，将未测混杂变量作为完全缺失变量插补，并讨论模型非识别、矛盾后验解及随机截距替代模型。
- 材料陈述的贡献
- 摘要报告了干预对九个月心血管健康有益的证据，同时指出未测混杂估计可能产生矛盾后验解，替代模型仍需进一步发展。
- 阅读关注点
- 重点核对随机分配如何支持多值暴露效应识别、先验对未测混杂的约束、非识别处理，以及健康效应区间的定义和敏感性。
- 阅读边界
- 这是 arXiv 预印本，同行评审和期刊接收未核实；所给摘要注明完整摘要另见文章，且未列出识别条件，不能据此排除非识别风险。
原文摘要
Using the PreventS trial data, our objective is to estimate average effects of a Health Wellness Coaching (HWC) intervention on improvement of cardiovascular health at 9 months post randomization and in three consecutive 3-month periods over 9 months post randomization. Conventional approaches, including instrumental variable models, are not applicable in the presence of multiple correlated multivalued exposures and unmeasured confounding. We propose a causal framework and its Bayesian modelling procedures to identify and estimate average effects of one or multiple multivalued exposures on one outcome in the presence of unmeasured confounding, noncompliance and missing data, in a two-arm randomized trial. We also propose estimation methods of unmeasured confounders, where the exposure and outcome distributions are conditional on unmeasured confounders and then unmeasured confounders are imputed as completely missing variables. Several types of model non-identifiability and possible solutions are described. There is a risk that estimation methods of unmeasured confounders can fail when multiple contradictory posterior solutions are produced. The random intercept outcome models that only adjust for unmeasured confounding in the outcome distribution are proposed as a good surrogate causal model in this case, and they need further development. There is evidence that the HWC intervention is beneficial to cardiovascular health at 9 months post randomization. On average, completing one HWC session improves the Life's Simple Seven total score by 0.16 (0.09, 0.22) and reduces systolic blood pressure by 0.54 (0.19, 0.90) mm Hg. There is also evidence that the HWC intervention has a larger beneficial effect on cardiovascular health during 3 months post randomization. There is no clear evidence that the HWC intervention benefits or harms mental health. The complete abstract is in the article.