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A note on testing conditional independence for social network analysis
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作者 PAN Rui WANG HanSheng 《Science China Mathematics》 SCIE CSCD 2015年第6期1179-1190,共12页
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 ... 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. 展开更多
关键词 independence validity conditional estimator assumption asymptotic likelihood rejection powerful exponential
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