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贝叶斯边际结构模型×贝叶斯双重差分法×
领域因果推断因果推断
方法族Regression modelRegression model
起源年份2015 (Bayesian extension); 2000 (MSM foundation)2015-2023
提出者Saarela, Stephens, Moodie & Klein (Bayesian extension); Robins, Hernan & Brumback (original MSM)Li & Marchand (formal Bayesian DiD framework); Brodersen et al. (Bayesian causal inference in time series)
类型Causal inference / Bayesian weighted regressionBayesian causal inference / panel regression
开创性文献Saarela, O., Stephens, D. A., Moodie, E. E. M., & Klein, M. B. (2015). On Bayesian estimation of marginal structural models. Biometrics, 71(2), 279-288. DOI ↗Li, F., & Marchand, J. (2023). Bayesian inference for difference-in-differences. Econometrics Journal, 26(3), 509-529. link ↗
别名Bayesian MSM, Bayesian MSM-IPW, Bayesian weighted structural model, Bayesian causal MSMBayesian DiD, Bayes DiD, Bayesian diff-in-diff, Bayesian panel causal estimator
相关65
摘要Bayesian Marginal Structural Model (Bayesian MSM) combines the causal identification power of inverse-probability-weighted marginal structural models with Bayesian posterior inference. Rather than relying on point estimates and asymptotic standard errors, it propagates uncertainty through a full posterior distribution over causal effect parameters, offering coherent uncertainty quantification for causal effects of time-varying treatments.Bayesian Difference-in-Differences applies Bayesian statistical inference to the classic DiD design, replacing frequentist point estimates with full posterior distributions over the treatment effect. This yields not only an estimate of the causal effect but also a coherent probability statement about its magnitude and uncertainty, making it especially useful when sample sizes are modest or informative prior knowledge is available.
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ScholarGate方法对比: Bayesian Marginal Structural Model · Bayesian Difference-in-Differences. 于 2026-06-15 检索自 https://scholargate.app/zh/compare