Erik-Jan van Kesteren

Van Kesteren, E. J., & Bergkamp, T. L. G. (In preparation). Bayesian Analysis of Formula One Race Results: Disentangling Driver Skill and Constructor Advantage.
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Van Kesteren, E. J., & Oberski, D. L. (Accepted). Flexible Extensions to Structural Equation Models using Computation Graphs. Structural Equation Modeling: A Multidisciplinary Journal.
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Van Kesteren, E. J., Sun, C., Oberski, D. L., Dumontier, M. J. & Ippel, G. J. E. (Under Review). Generalized linear models on vertically partitioned data using distributed block coordinate descent.
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Van Kesteren, E. J., & Kievit, R. K. (2020). 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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Ly, A., Stefan, A., van Doorn, J., Dablander, F., van den Bergh, D., Sarafoglou, A., …, Van Kesteren, E. J., … & Wagenmakers, E. J. (2020). The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P-value Hypothesis Test. Computational Brain & Behavior
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Wagenmakers, E. J., Love, J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., …, Van Kesteren, E. J., … & Morey, R.D. (2018). Bayesian inference for psychology. Part II: Example applications with JASP. Psychonomic Bulletin & Review, 25(1), 58-76. doi: 10.3758/s13423-017-1323-7
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In preparation / submitted

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