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Regression modelDyadic network inference

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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Sources

  1. 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
  2. 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

How to cite this page

ScholarGate. (2026, June 22). Multiple Regression Quadratic Assignment Procedure (MRQAP). ScholarGate. https://scholargate.app/en/sociology/mrqap-network-regression

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ScholarGateMRQAP Network Regression (Multiple Regression Quadratic Assignment Procedure (MRQAP)). Retrieved 2026-06-24 from https://scholargate.app/en/sociology/mrqap-network-regression · Dataset: https://doi.org/10.5281/zenodo.20539026