Порівняння методів

	Центральний аналіз	Метод інструментальних змінних (ІЗ) для причинно-наслідкового висновку
Галузь	Мережевий аналіз	Економіка охорони здоров'я
Родина	Process / pipeline	Process / pipeline
Рік появи	1979	1990s (modern applications)
Автор методу	Linton C. Freeman	Angrist & Pischke (applied econometrics); rooted in econometric theory
Тип	Descriptive / exploratory network measure family	Method
Основоположне джерело	Freeman, L.C. (1979). Centrality in Social Networks: Conceptual Clarification. Social Networks, 1(3), 215-239.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Інші назви	Merkeziyet Analizi (Degree, Betweenness, Eigenvector), node centrality, centrality measures, graph centrality	IV, two-stage least squares, TSLS, causal estimation
Пов'язані	5	3
Підсумок	Centrality analysis is a family of network-analytic measures, formalized by Freeman (1979), that quantifies the structural importance of individual nodes within a graph. Each centrality index captures a distinct mechanism of influence: degree centrality reflects direct connectivity, betweenness centrality identifies nodes that broker information flow, closeness centrality captures proximity to all others, and eigenvector centrality (along with PageRank) rewards connection to highly connected neighbors.	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.