So sánh phương pháp

	Mô hình cấu trúc biên tế đánh giá chính sách	Trọng số Xác suất Nghịch đảo của Điều trị (IPW / IPTW)
Lĩnh vực	Suy luận nhân quả	Suy luận nhân quả
Họ	Regression model	Regression model
Năm ra đời	2000	2000
Người khởi xướng	James M. Robins, Miguel A. Hernan, Babette Brumback	Robins, Hernán & Brumback
Loại	Causal inference / weighted regression	Causal inference weighting estimator
Công trình gốc	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., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560.
Tên gọi khác	MSM for policy evaluation, policy MSM, causal MSM, structural policy weighting model	IPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
Liên quan	6	5
Tóm tắt	A Policy Evaluation Marginal Structural Model (MSM) is a causal inference framework that estimates the population-average effect of a policy by using inverse probability weighting to create a pseudo-population in which treatment assignment is independent of measured confounders, enabling unbiased comparison of potential outcomes under different policy scenarios from observational data.	Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.