手法を比較

	パネルデータ周辺構造モデル（MSM）	Marginal Structural Model (MSM)
分野	因果推論	因果推論
系統	Regression model	Regression model
提唱年	2000	2000
提唱者	James M. Robins, Miguel A. Hernan, Babette Brumback	James M. Robins, Miguel A. Hernan, Babette Brumback
種類	Causal model for time-varying treatments	Causal model / semiparametric weighting
原典	Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560.	Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560.
別名	MSM panel, longitudinal MSM, panel MSM, time-varying treatment MSM	MSM, MSM-IPTW, marginal structural Cox model, weighted structural model
関連	5	5
概要	A panel data marginal structural model (MSM) uses inverse probability of treatment weighting (IPTW) across multiple time periods to estimate the causal effect of a time-varying treatment, while appropriately adjusting for time-varying confounders that are themselves affected by prior treatment — a bias source that conventional regression cannot handle.	A marginal structural model is a causal modeling framework designed to estimate the effect of a time-varying treatment in the presence of time-varying confounders that are themselves affected by prior treatment. By reweighting observations with inverse probability of treatment weights, MSMs create a pseudo-population in which confounding is eliminated, enabling unbiased estimation of causal treatment contrasts even when standard regression adjustments would fail.