Сравнение методов

	Анализ центральности	Метод инструментальных переменных (ИП) для причинно-следственного вывода
Область	Сетевой анализ	Экономика здравоохранения
Семейство	Process / pipeline	Process / pipeline
Год появления	1979	1990s (modern applications)
Автор метода	Linton C. Freeman	Angrist & Pischke (applied econometrics); rooted in econometric theory
Тип	Descriptive / exploratory network measure family	Method
Основополагающий источник	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.
Другие названия	Merkeziyet Analizi (Degree, Betweenness, Eigenvector), node centrality, centrality measures, graph centrality	IV, two-stage least squares, TSLS, causal estimation
Связанные	5	3
Сводка	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.