So sánh phương pháp

	Mô hình cấu trúc biên trong nghiên cứu giáo dục	Phương pháp Biến Công cụ (IV) cho Suy luận Nhân quả
Lĩnh vực	Suy luận nhân quả	Kinh tế học y tế
Họ	Regression model	Process / pipeline
Năm ra đời	2000 (method); 2006 (canonical education application)	1990s (modern applications)
Người khởi xướng	James M. Robins, Miguel A. Hernán, Babette Brumback (epidemiology); Guanglei Hong & Stephen Raudenbush (education application)	Angrist & Pischke (applied econometrics); rooted in econometric theory
Loại	Causal inference / weighted regression model	Method
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.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Tên gọi khác	MSM, marginal structural model, MSM with inverse probability weighting, IPW-MSM	IV, two-stage least squares, TSLS, causal estimation
Liên quan	5	3
Tóm tắt	A marginal structural model (MSM) is a causal inference technique that uses inverse probability weighting to estimate the effect of a treatment or educational intervention that changes over time. Introduced by Robins, Hernán and Brumback (2000) in epidemiology and brought into education by Hong and Raudenbush (2006), MSMs handle time-varying confounding — a challenge that conventional regression cannot resolve.	Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes.