Title: Latent Space Model for Aggregated Relational Data
Abstract: Aggregated Relational Data (ARD) are indirect network data collected using survey questions of the form "how many X's do you know?" It is most often used to estimate the size of populations that are difficult to count directly and allows researchers to choose specific subpopulations of interest without sampling or surveying members of these subpopulations directly. What has been under-utilized is the indirect information on social structure captured by ARD. In this talk, I present a latent space model and Bayesian computation framework for inference and estimation of social structures using ARD from non-network samples in social networks, the variation of social structures in subnetworks, and the relations between (hard-to-reach) subpopulations.