Prof. Dr. Felix Schönbrodt
Managing Director of the OSC
Faculty of Psychology & Education
Mission Statement
I am principal investigator for Psychological Methods and Assessment at the Department of Psychology, the managing director of the LMU Open Science Center, and steering group member of the META-REP priority program (‘A meta-scientific research program to analyze and optimize replicability in the behavioral, social, and cognitive Sciences’).
The reproducibility of research findings is a core criterion of science, which however, has been challenged by the failure of recent large-scale replication projects. To foster open science practices, I teamed up with colleagues and established our department’s “Open Science Committee” in 2015. The outcomes of this committee include an open science paragraph which we included in all recent professorship job descriptions, adding transparency criteria to the department’s performance-based funding scheme, or introducing modules on preregistrations, open data, and reproducible scripts as mandatory components in undergraduate courses.
Together with the board of the German Psychological Society (DGPs) I developed the society’s recommendations for data sharing in psychology [English version], which have been updated in 2020 (DGPs-Kommission “Open Science”, 2020). In 2016, I received the Leamer-Rosenthal-Prize for Open Social Science from the Berkeley Initiative for Transparency in the Social Sciences (BITSS).
In the DFG-funded META-REP project “From ‘Academic works’ to ‘Working in academia’” we are analyzing reform proposals for academia in an agent-based modelling approach.
Research Interests
Selected Publications
2025
Responsible Research Assessment I: Implementing DORA and CoARA for hiring and promotion in psychology
Meta-Psychology
DOI2023
Big little lies: a compendium and simulation of p-hacking strategies
Royal Society Open Science, 10, 220346
DOI2019
Correcting for Bias in Psychology: A Comparison of Meta-Analytic Methods
Advances in Methods and Practices in Psychological Science, 2, 115-144
DOI2017
Bayes factor design analysis: Planning for compelling evidence
Psychonomic Bulletin & Review, 25, 128–142
DOI