Bayesian inference for causal mechanisms with application to a randomized study for postoperative pain control
Bayesian inference for causal mechanisms with application to a randomized study for postoperative pain control
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因果机制的贝叶斯推断及其应用于术后疼痛控制随机研究
DOI：
10.1093/biostatistics/kxx010
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发表时间：
2017
期刊：
影响因子：
2.1
通讯作者：
F. Mealli
中科院分区：
文献类型：
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作者：
M. Baccini;Alessandra Mattei;F. Mealli
摘要 我们进行了主要分层和中介分析，以调查在一项前瞻性、随机、双盲研究中，患者术后自行静脉注射镇痛在多大程度上介导了治疗对术后疼痛控制的积极总体效果。使用贝叶斯方法进行推理，我们估计主分层中产生的关联和分离主层效应，以及中介分析的自然效应。我们强调，主要分层和中介分析侧重于不同的因果估计值，回答不同的因果问题，并涉及不同的结构假设集。
Summary 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.
DOI：
10.1097/ede.0000000000000034
发表时间：
2014-03
期刊：
Epidemiology (Cambridge, Mass.)
影响因子：
--
作者：
Vanderweele TJ;Vansteelandt S;Robins JM
通讯作者：
Robins JM