Die vielen Gesichter von GESIS
Vita
I am a Postdoc in the team "Transparent Social Analytics" in the department of "Computational Social Science" at "GESIS - Leibniz Institute for the Social Sciences".I did my PhD on Bayesian statistics applied to biomedical research at the University of Groningen, The Netherlands. Before that, I completed a BSc in Psychology and a MSc in Behavioural and Cognitive Neurosciences, both at the University of Groningen.
Service
I serve as one of two managing editors for the journal methods, data, analyses (mda).Forschung
My research focuses on Bayesian modelling and its application to social phenomena. Furthermore, I am interested in multiverse analysis.Veröffentlichungen
Zeitschriftenaufsatz
Linde, Maximilian, Jorge N. Tendeiro, and Don van Ravenzwaaij. 2025. "Bayes factors for two-group comparisons in Cox regression with an application for reverse-engineering raw data from summary statistics." Journal of Applied Statistics online first: 1-25. doi: https://doi.org/10.1080/02664763.2025.2472150.
Linde, Maximilian, Laura Jochim, Jorge N. Tendeiro, and Don van Ravenzwaaij. 2025 (Forthcoming). "Data-driven prior elicitation for Bayes factors in Cox regression for nine subfields in biomedicine." PLoS ONE: .
van Minnen, Olivier, Maximilian Linde, Annemieke Oude Lansink-Hartgring, Bas van den Boogaard, Jeroen J. H. Bunge, Thijs S. R. Delnoij, Carlos V. Elzo Kraemer, Marijn Kuijpers, Jacinta J. Maas, Jesse de Metz, Marcel van de Poll, Dinis dos Reis Miranda, Alexander P. J. Vlaar, Don van Ravenzwaaij, and Walter M. van den Bergh. 2025. "Reduced anticoagulation targets in extracorporeal life support (RATE): Protocol for a pre-planned secondary Bayesian analysis of the rate trial." Trials 26 (15 March 2025): 90. doi: https://doi.org/10.1186/s13063-025-08737-6.
Linde, Maximilian, Jorge N. Tendeiro, Eric-Jan Wagenmakers, and Don van Ravenzwaaij. 2024. "Practical implications of equating equivalence tests: Reply to Campbell and Gustafson (2022)." Psychological Methods 29 (3): 603-605. doi: https://doi.org/10.1037/met0000549.
Linde, Maximilian, Merle-Marie Pittelkow, Nina R. Schwarzbach, and Don van Ravenzwaaij. 2024. "Reputation without practice: A dynamic computational model of the unintended consequences of open scientist reputations." Journal of Trial and Error 4 (1): 82-110. doi: https://doi.org/10.36850/mr10.
Pittelkow, Merle-Marie, Maximilian Linde, Ymkje Anna de Vries, Lars G. Hemkens, Andreas M. Schmitt, Rob R. Meijer, and Don van Ravenzwaaij. 2024. "Strength of statistical evidence for the efficacy of cancer drugs: A Bayesian reanalysis of randomized trials supporting Food and Drug Administration approval." Journal of Clinical Epidemiology 174 (October 2024): 111479. doi: https://doi.org/10.1016/j.jclinepi.2024.111479.
Heck, D.W., U. Boehm, F. Böing-Messing, P. C. Bürkner, K. Derks, Z. Dienes, Q. Fu, X. Gu, D. Karimova, H. A. L. Kiers, I. G. Klugkist, R. M. Kuiper, M. D. Lee, R. Leenders, H. J. Leplaa, Maximilian Linde, A. Ly, M. Meijerink-Bosman, M. Moerbeek, J. Mulder, B. Palfi, F. D. Schönbrodt, J. N. Tendeiro, D. van den Bergh, C. van Lissa, D. van Ravenzwaaij, W. Vanpaemel, E.-J. Wagenmakers, D. R. Williams, M. Zondervan-Zwijnenburg, and H. Hoijtink. 2023. "A review of applications of the Bayes factor in psychological research." Psychological Methods 28 (3): 558-579. doi: https://doi.org/10.1037/met0000454.
Linde, Maximilian, and Don van Ravenzwaaij. 2023. "Bayes factor model comparisons across parameter values for mixed models." Computational Brain & Behavior 6 (1): 14-27. doi: https://doi.org/10.1007/s42113-021-00117-y.
van Doorn, Johnny, Julia M. Haaf, Angelika M. Stefan, Eric-Jan Wagenmakers, Gregory Edward Cox, Clintin P. Davis-Stober, Andrew Heathcote, Daniel W. Heck, Michael Kalish, David Kellen, Dora Matzke, Richard D. Morey, Bruno Nicenboim, Don van Ravenzwaaij, Jeffrey N. Rouder, Daniel J. Schad, Richard M. Shiffrin, Henrik Singmann, Shravan Vasishth, João Veríssimo, Florence Bockting, Suyog Chandramouli, John C. Dunn, Quentin F. Gronau, Maximilian Linde, Sara D. McMullin, Danielle Navarro, Martin Schnuerch, Himanshu Yadav, and Frederik Aust. 2023. "Bayes factors for mixed models: A discussion." Computational Brain & Behavior 6 (1): 140-158. doi: https://doi.org/10.1007/s42113-022-00160-3.
Linde, Maximilian, and Don van Ravenzwaaij. 2023. "baymedr: an R package and web application for the calculation of Bayes factors for superiority, equivalence, and non-inferiority designs." BMC Medical Research Methodology 23 (24 November 2023): 279. doi: https://doi.org/10.1186/s12874-023-02097-y.
Linde, Maximilian, Jorge N. Tendeiro, Ravi Selker, Eric-Jan Wagenmakers, and Don van Ravenzwaaij. 2023. "Decisions about equivalence: A comparison of TOST, HDI-ROPE, and the Bayes factor." Psychological Methods 28 (3): 740-755. doi: https://doi.org/10.1037/met0000402.
Neumann, Marvin, A. Susan M. Niessen, Maximilian Linde, Jorge N. Tendeiro, and Rob R. Meijer. 2023. "“Adding an egg” in algorithmic decision making: improving stakeholder and user perceptions, and predictive validity by enhancing autonomy." European Journal of Work and Organizational Psychology (33): 245-262. doi: https://doi.org/10.1080/1359432X.2023.2260540.
Beitrag nicht auf Konferenz
Linde, Maximilian. 2023. "Bayesian statistics: A gentle introduction." Guest lecture for the Master course Advanced Organisational Research Skills at Vrije Universiteit Amsterdam, online, 2023-11-08.
Veranstaltung
Linde, Maximilian, Gabriella Lapesa, and Danica Radovanović. 2024. "Reflecting on Research Workflows Across Disciplines." MethodsNET Conference, Université catholique de Louvain, 2024-10-30 - 2024-11-01.