方法证据记录
Robust Marginal Structural Model
Robust Marginal Structural Models (robust MSMs) extend the standard MSM framework — which uses inverse probability of treatment weighting to handle time-varying confounding — by pairing IPTW estimation with sandwich (robust) standard errors or doubly-robust estimators. This combination yields valid causal estimates and reliable inference even when the outcome regression model is mildly misspecified or weights are moderately variable.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Robust Marginal Structural Model with Stabilized Inverse Probability Weighting
分类方法记录 · regression-model / causal-inference
- Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. · DOI 10.1097/00001648-200009000-00011
- Hernán, M. A., & Robins, J. M. (2020). Causal Inference: What If. Chapman & Hall/CRC. · URL
精选声明
声明已持久化到证据分类账中,每个声明都有自己的评估。
尚无精选声明
当分类账中没有声明时,此视图不会自行创建声明评估。
相关方法
从方法图中生成,显示为机器建议的关系 — 不推断任何证据声明。