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

See all articles by Rui Pan

Rui Pan

Peking University

Hansheng Wang

Peking University - Guanghua School of Management

Multiple version iconThere are 2 versions of this paper

Date Written: May 4, 2015

Abstract

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

Pan, Rui and Wang, Hansheng, A Note on Testing Conditional Independence for Social Network Analysis (May 4, 2015). Science China Mathematics, Vol. 58, No. 6, June 2015. Available at SSRN: https://ssrn.com/abstract=2602604

Rui Pan

Peking University ( email )

No. 38 Xueyuan Road
Haidian District
Beijing, Beijing 100871
China

Hansheng Wang (Contact Author)

Peking University - Guanghua School of Management ( email )

Peking University
Beijing, Beijing 100871
China

HOME PAGE: http://hansheng.gsm.pku.edu.cn

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