Collecting some of my recent talks and workshops. More talk and workshop material can be found in the OSF project of our LMU Munich Open Science Initiative, in my personal OSF project, and at the LMU Open Science Center.

Meta-Science / Open Science

2023: Responsible Research Assessment: A practical recommendation for the evaluation of research quality beyond h-index and journal impact factors [Slides]

2022: When the evolution of science fails: On runaway selection and severe testing evasion [Slides]

2022: Open Science, metrics, and academic careers [Slides]

2022: Quality assurance and Skin in the Game: How to setup structures that prevent misconduct and foster good science [Slides]

2022: From „the replication crisis” to „the credibility revolution” in psychological science? What have we achieved, where do we go? [Slides]

2021: Quality assurance and control in academia [Slides]

2021: How to share psychological research data: Revised recommendations from the German Psychological Society [Slides]

2019: Moving a scientific community towards data sharing: Experiences from the data management recommendations of the German Psychological Society [Slides]

2018: Don’t make a fool of yourself: Reputation and performance evaluation in academia [Slides]

2018: Beyond bean/publication counting: Performance evaluation and hiring criteria that foster good science [Slides]


2021 (Talk): The leapfrog design: An Adaptive Bayesian Design for rapid treatment development [Slides]

2021 (Talk): Correcting for bias in the literature: A comprehensive comparison of meta-analytic methods for bias-correction in psychology (aka: Meta-analyses are fucked). [Slides]

2020 (Talk): Sequential Bayes Factors guarantee compelling evidence: Efficient designs under uncertainty [Slides][R package BFDA]

2019 (Workshop, 6h): Maintaining privacy with open data (together with Anton Marx, LMU) [Slides]

2018 (Workshop, 7-8h): Sequential Hypothesis Testing with Bayes Factors [Slides][R package BFDA]

2018 (Talk): Testing similarity effects with dyadic response surface analysis (DRSA) [Slides][R package RSA]

2017 (Talk): < .005: Redefine statistical significance with Double-ohh-five [Slides]

Motivation Science

2021: Automatic coding of German PSE stories using machine learning algorithms [Slides][Demo Shiny App]