Social Network Models and Missing Data

I am currently developing a model for three-way network data.

I pursue three major streams of research:

• Three-way data structures

• Missing network data treatments

• Effect sizes for networks

In my PhD project I developed and evaluated algorithms for handling missing social network data (missing information on the links between actors and actor attributes). My work focuses on the most used network models in the social sciences, exponential random graph models, and stochastic actor-oriented models. For both I developed, evaluated, and implemented algorithms to reduce bias in parameter estimation under missing data, as well as provide proper multiple imputation for subsequent analysis.


Social Network Analysis (SAOM, ERGM, BERGM), Missing Data, R programming, Statistics


2019 - Postdoc at the Institute for Analytical Sociology, Linköping University, Linköping, Sweden

2015 – 2019 PhD at the department of sociology, University of Groningen, Groningen, The Netherlands

2013 – 2015 Research M.Sc. Behavioural Sciences, Radboud University, Nijmegen, The Netherlands

2010 – 2013 B.Sc. Psychology – Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany

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Bringmann, L., Elmer, T., Epskamp, S., Krause, R.W., Schoch, D., Wichers, M., Wingman, J., & Snippe, E. (2019). What do centrality measures measure in psychological networks? Journal of Abnormal Psychology.

Krause, R. W., Huisman, M., Steglich, C.E.G., & Snijders, T. A. B. (2018). Missing network data – a comparison of different Imputation methods. IEEE/ACM Proceedings ASONAM 2018, 159 – 163.

Krause, R. W., Huisman, M., & Snijders, T. A. B. (2018). Multiple imputation for longitudinal network data. Statistica Applicata - Italian Journal of Applied Statistics , 30(1), 33-57. DOI: 10.26398/IJAS.0030-002

Krause, R. W., & Caimo, A. (2019, March). Missing Data Augmentation for Bayesian Exponential Random Multi-Graph Models. In International Workshop on Complex Networks (pp. 63-72). Springer,Cham.

Open Science Collaboration (2015). PSYCHOLOGY. Estimating the reproducibility of psychological science. Science , 349(6251), [aac4716]. DOI: 10.1126/science.aac4716