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Abstract:
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The network scale-up method based on ``how many X's do you know?'' questions has gained popularity in estimating the sizes of hard-to-reach populations. The success of the method relies primarily on the easy nature of the data collection and the flexibility of the procedure, especially since the model does not require a sample from the target population, a major limitation of traditional size estimation models. New versions of the method also move beyond population sizes, producing estimates for network sizes, highlighting relationships between subpopulations, and illustrating biases in social networks. In this article, we propose a new network scale-up model which incorporates respondent and subpopulation covariates in a regression framework, includes a bias term that more accurately estimates biases under fewer assumptions, and adds a correlation structure between subpopulations that is present in network models but was missing from previous network scale-up models. Our proposed model answers two fundamental questions in the network scale-up method literature: what role predictors have on the response and how subpopulations relate to one another.
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