Erik-Jan van Kesteren

Schram, R. D., Volker, T. B., Bagheri, A. B., Scholten, R., Spithorst, S., & Van Kesteren, E.-J. (In preparation). Metasynth: Transparent Generation of Synthetic Tabular Data with Privacy Guarantees.
Preprint code

Lugtig, P., Timmers, A., & Van Kesteren, E.-J. (In preparation). Correcting Inferences for Volunteer-Collected Data with Geospatial Sampling Bias.
Preprint code

Volker, T. B., de Wolf, P. P., & van Kesteren, E.-J. (2023) Assessing the Utility of Synthetic Data: A Density Ratio Perspective UNECE Expert meeting on Statistical Data Confidentiality
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Van Kesteren, E.-J., & Bergkamp, T. L. G. (2023). Bayesian Analysis of Formula One Race Results: Disentangling Driver Skill and Constructor Advantage.
Journal of Quantitative Analysis in Sports. doi: 10.1515/jqas-2022-0021
Preprint code

Van Kesteren, E.-J., & Oberski, D. L. (2022). Flexible Extensions to Structural Equation Models using Computation Graphs. Structural Equation Modeling: A Multidisciplinary Journal. doi: 10.1080/10705511.2021.1971527
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Van Kesteren, E.-J., & Kievit, R. K. (2021). Exploratory factor analysis with structured residuals for brain network data. Network Neuroscience. doi: 10.1162/netn_a_00162
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Boeschoten, L., Van Kesteren, E.-J., Bagheri, A., & Oberski, D. L. (2020). Achieving Fair Inference Using Error-Prone Outcomes. International Journal of Interactive Multimedia and Artificial Intelligence. doi: 10.9781/ijimai.2021.02.007
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Van Kesteren, E.-J., & Oberski, D.L. (2019) Mediation analysis with many potential mediators. Structural Equation Modeling: A Multidisciplinary Journal. doi: 10.1080/10705511.2019.1588124
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In preparation / submitted

Main publications