Focused model selection for social networks

Abstract

We present a focused selection method for social networks. The procedure is driven by a focus, the main quantity we want to estimate well. It represents the statistical translation of a research hypothesis into parameters of interest. Given a collection of models, the procedure estimates for each model the mean squared error of the estimator of the focus. The model with the smallest such value is selected. We present focused model selection for (i) exponential random graph models, (ii) network autocorrelation models and (iii) network regression models to investigate existing relations in social networks. Worked-out examples illustrate the methodology.