Krahasoni metodat

	Metoda e Variablave Instrumentalë (IV) për Inferencën Kauzale	Modeli i Zinxhirit të Markovit në Ekonominë e Shëndetësisë
Fusha	Ekonomia shëndetësore	Ekonomia shëndetësore
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1990s (modern applications)	1983
Krijuesi	Angrist & Pischke (applied econometrics); rooted in econometric theory	Beck & Pauker (medical decision analysis, Massachusetts General Hospital)
Lloji	Method	Method
Burimi themelues	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.	Beck, J. R., & Pauker, S. G. (1983). The Markov Process in Medical Prognosis. Medical Decision Making, 3(4), 419-458.
Emërtime të tjera	IV, two-stage least squares, TSLS, causal estimation	Markov model, state transition model, cohort simulation
Të lidhura	3	5
Përmbledhja	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.	A Markov model is a decision-analytic tool that simulates disease progression through defined health states over time, calculating cumulative costs and quality-adjusted life years (QALYs) to enable cost-effectiveness analysis. Developed by Beck and Pauker in 1983, Markov models are now the standard framework for projecting long-term outcomes of health interventions, especially chronic diseases where patients transition between clinical states (treatment response, disease progression, remission, death). Used by health technology assessment bodies and pharmaceutical companies to predict intervention value beyond trial duration.