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Diagnosing Multicollinearity in Exponential Random Graph Models
Exponential random graph models (ERGM) have been widely applied in the social sciences in the past ten years. However, diagnostics for ERGM have lagged behind their use. Collinearity-type problems can emerge without detection when fitting ERGM, skewing coefficients, biasing standard errors, and yielding inconsistent model estimates. This article provides a method to detect multicollinearity in ERGM. It outlines the problem and provides a method to calculate the variance inflation factor fromdoi:10.31235/osf.io/2tgm7 fatcat:4qvnhgzcq5btfm7uhko5isw77q