Usporedite metode

	Mendelovska randomizacija	Dizajn diskontinuiteta regresije (RDD)
Područje	Uzročno zaključivanje	Uzročno zaključivanje
Obitelj	Regression model	Regression model
Godina nastanka	1997	2008
Tvorac	George Davey Smith	Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)
Vrsta	Genetic instrumental variable framework	Quasi-experimental causal design
Temeljni izvor	Davey Smith, G., & Hemani, G. (2014). Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Human Molecular Genetics, 23(R1), R89-R98.	Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635.
Drugi nazivi	MR	RDD, regression discontinuity design, sharp RDD, fuzzy RDD
Srodne	2	5
Sažetak	Mendelian randomization is a method for estimating causal effects of exposures on outcomes using genetic variants as instrumental variables. Introduced by George Davey Smith in the 1990s, it exploits Mendel's law of segregation to remove confounding bias. It has become a cornerstone technique in epidemiological causal inference.	Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold.