Causal Inference using Multivariate Generalized Linear Mixed-Effects Models with Longitudinal Data
利用多元广义线性混合效应模型开展纵向数据因果推断AI 解读 ↓
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利用多元广义线性混合效应模型开展纵向数据因果推断
- 研究问题
- 在存在选择偏差和未测量混杂的观察性纵向数据中，如何结合个体特征与历史信息，评估不同动态治疗方案的亚组反事实收益？
- 方法与思路
- 作者将贝叶斯 g-computation 与多元广义线性混合效应模型结合，通过联合建模和个体随机效应表示时间不变的未测量因素。
- 材料陈述的贡献
- 摘要称，方法允许时间不变的未测量混杂，并提出基于治疗分配异质性的序贯可忽略性假设，以模拟和硬皮病临床资料展示应用。
- 阅读关注点
- 应核对随机效应如何获得识别、序贯可忽略性的精确定义，以及联合模型误设时的敏感性；尤其关注未测量因素为何限定为时间不变。
- 阅读边界
- 这是 arXiv 预印本，同行评审或期刊接收未核实；摘要未说明完整识别条件，不能认为随机效应自动消除了所有未测量混杂。
原文摘要
Dynamic prediction of causal effects under different treatment regimes conditional on an individual's characteristics and longitudinal history is an essential problem in precision medicine. This is challenging in practice because outcomes and treatment assignment mechanisms are unknown in observational studies, an individual's treatment efficacy is a counterfactual, and the existence of selection bias is often unavoidable. We propose a Bayesian framework for identifying subgroup counterfactual benefits of dynamic treatment regimes by adapting Bayesian g-computation algorithm (J. Robins, 1986; Zhou, Elliott, & Little, 2019) to incorporate multivariate generalized linear mixed-effects models. Unmeasured time-invariant factors are identified as subject-specific random effects in the assumed joint distribution of outcomes, time-varying confounders, and treatment assignments. Existing methods mostly assume no unmeasured confounding and focus on balancing the observed confounder distributions between different treatments, while our method allows the presence of time-invariant unmeasured confounding. We propose a sequential ignorability assumption based on treatment assignment heterogeneity, which is analogous to balancing the latent tendency toward each treatment due to unmeasured time-invariant factors beyond the observables. We use simulation studies to assess the sensitivity of the proposed method's performance to various model assumptions. The method is applied to observational clinical data to investigate the efficacy of continuously using mycophenolate in different subgroups of scleroderma patients who were treated with the drug.