A Note on Testing Conditional Independence for Social Network Analysis
Science China Mathematics, Vol. 58, No. 6, June 2015
12 Pages Posted: 5 May 2015
Date Written: May 4, 2015
In social network analysis, logistic regression models have been widely used to establish the relationship between the response variable and covariates. However, such models often require the network relationships to be mutually independent, after controlling for a set of covariates. To assess the validity of this assumption, we propose test statistics, under the logistic regression setting, for three important social network drivers. They are, respectively, reciprocity, centrality, and transitivity. The asymptotic distributions of those test statistics are obtained. Extensive simulation studies are also presented to demonstrate their finite sample performance and usefulness.
Keywords: centrality, conditional independence, logistic regression model, reciprocity, social network analysis, transitivity
JEL Classification: C3
Suggested Citation: Suggested Citation