Missing data in networks: Exponential random graph (p*) models for networks with non-respondents

Abstract

Survey studies of complete social networks often involve non-respondents, whereby certain people within the "boundary" of a network do not complete a sociometric questionnaire - Either by their own choice or by the design of the study - Yet are still nominated by other respondents as network partners. We develop exponential random graph (p*) models for network data with non-respondents. We model respondents and non-respondents as two different types of nodes, distinguishing ties between respondents from ties that link respondents to non-respondents. Moreover, if we assume that the non-respondents are missing at random, we invoke homogeneity across certain network configurations to infer effe..