Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Анализ на централност× | Метод на инструменталните променливи (IV) за причинно-следствен анализ× | |
|---|---|---|
| Област≠ | Мрежови анализ | Икономика на здравеопазването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1979 | 1990s (modern applications) |
| Създател≠ | Linton C. Freeman | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| Тип≠ | Descriptive / exploratory network measure family | Method |
| Основополагащ източник≠ | Freeman, L.C. (1979). Centrality in Social Networks: Conceptual Clarification. Social Networks, 1(3), 215-239. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| Други названия | Merkeziyet Analizi (Degree, Betweenness, Eigenvector), node centrality, centrality measures, graph centrality | IV, two-stage least squares, TSLS, causal estimation |
| Свързани≠ | 5 | 3 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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