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
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…