Abstract:
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The statistical analysis of social networks is increasingly used to understand social processes and patterns. The association between social relationships and individual behaviors is of particular interest to sociologists, psychologists, and public health researchers. Several recent network studies make use of the fixed choice design (FCD), which induces missing edges in the network data. Due to the complex dependence structure inherent in networks, missing data can pose very difficult problems for valid statistical inference. In this paper we introduce novel methods for accounting for the FCD censoring and introduce a new survey design, which we call the Augmented Fixed Choice Design (AFCD). The AFCD adds considerable information to analyses without unduly burdening the survey respondent, resulting in improvements over the FCD. We demonstrate this new method through simulation studies and an analysis of a network of undergraduates living in a residence hall.
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