In a well-known paper Social Networks 1 (1979) 215 Linton Freeman clarified the importance of the centrality concept in network analysis. There are a variety of centrality measures available, and they are mainly used as descriptive statistics in various network studies. For instance, actor centrality measured by vertex degree captures those aspects of centrality that have an impact on contacts given or received by the actor. The approach taken here is to consider actor centrality as a latent property that manifests itself in generating a particular network structure, and in order to measure centrality we are bound to rely on observable features of this network. By borrowing ideas from recent link-tracing survey methodology, we illustrate how probabilistic network models with centrality parameters can be used to improve on estimators and predictors of various actor attributes related to centrality.