Bandingkan kaedah

	Model Struktur Marginal dalam Penyelidikan Pendidikan	Kaedah Pemboleh Ubah Instrumental (IV) untuk Inferensi Kausal
Bidang	Inferens Kausal	Ekonomi Kesihatan
Keluarga	Regression model	Process / pipeline
Tahun asal	2000 (method); 2006 (canonical education application)	1990s (modern applications)
Pengasas	James M. Robins, Miguel A. Hernán, Babette Brumback (epidemiology); Guanglei Hong & Stephen Raudenbush (education application)	Angrist & Pischke (applied econometrics); rooted in econometric theory
Jenis	Causal inference / weighted regression model	Method
Sumber perintis	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.
Alias	MSM, marginal structural model, MSM with inverse probability weighting, IPW-MSM	IV, two-stage least squares, TSLS, causal estimation
Berkaitan	5	3
Ringkasan	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.