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Bayesian inference for causal mechanisms with application to a randomized study for postoperative pain control

机译:贝叶斯推断因果机制应用于术后疼痛控制的随机研究

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摘要

We conduct principal stratification and mediation analysis to investigate to what extent the positive overall effect of treatment on postoperative pain control is mediated by postoperative self administration of intra-venous analgesia by patients in a prospective, randomized, double-blind study. Using the Bayesian approach for inference, we estimate both associative and dissociative principal strata effects arising in principal stratification, as well as natural effects from mediation analysis. We highlight that principal stratification and mediation analysis focus on different causal estimands, answer different causal questions, and involve different sets of structural assumptions.
机译:我们进行主要分层和调解分析,以调查术后疼痛对照的阳性整体效果在多大程度上,患者在预期的,随机的双盲研究中患者术后自我镇痛介导。 利用贝叶斯方法推断,我们估计主要分层中出现的关联和分离主层效应,以及来自调解分析的自然影响。 我们强调,主要分层和调解分析重点关注不同的因果估计,回答不同的因果问题,涉及不同的结构假设。

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