Johan Koskinen                                                                             

         

                   

Johan Koskinen got his PhD in Statistics from Stockholm University and has since worked at the Departments of Sociology and Statistics, Stockholm University, The Swedish Institute for Social Research, and in the MelNet group, University of Melbourne. He currently works at ReMiSS, Department of Politics and International Relations, University of Oxford, and is a Non-Stipendiary Research Fellow of Nuffield College. Among his research interests are Bayesian inference for social networks, multilevel analysis, and missing data in event history models. Of particular interest are modelling and inference issues for different types of social networks in varying contexts and circumstances, with recent applications including single instances of networks and networks repeatedly observed through time and by different observers; in circumstances that allow for missing data and measurement error. In the Dynet project he is currently working together with Tom Snijders, Ruth Ripley, and John Light on models and inference procedures that may capture contextual differences and heterogeneity in social networks.