MRQAP Network Regression
Multiple regression quadratic assignment procedure (MRQAP) extends QAP to the regression setting: it predicts a dependent relational matrix from several independent relational matrices on the same actors — for example, modeling who collaborates with whom as a function of who is co-located, who shares a department, and who has prior friendship. Coefficients are estimated by ordinary least squares on the vectorized matrices, but significance is assessed by permutation, because dyadic dependence invalidates the standard regression standard errors.
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Vyanzo
- Krackhardt, D. (1988). Predicting with networks: Nonparametric multiple regression analysis of dyadic data. Social Networks, 10(4), 359–381. DOI: 10.1016/0378-8733(88)90004-4 ↗
- Dekker, D., Krackhardt, D., & Snijders, T. A. B. (2007). Sensitivity of MRQAP tests to collinearity and autocorrelation conditions. Psychometrika, 72(4), 563–581. DOI: 10.1007/s11336-007-9016-1 ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 22). Multiple Regression Quadratic Assignment Procedure (MRQAP). ScholarGate. https://scholargate.app/sw/sociology/mrqap-network-regression
Mbinu ipi?
Weka mbinu hii kando ya jamaa zake wa karibu na uzisome bega kwa bega — maktaba huweka vitabu mezani; uamuzi ni wako.
- Dyadic AnalysisSociology↔ linganisha
- Network Autocorrelation ModelSociology↔ linganisha
- Quadratic Assignment ProcedureSociology↔ linganisha
- Uchambuzi wa Mitandao ya KijamiiUchanganuzi wa Mitandao↔ linganisha
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