Open Science, Psychology, and the Art of Not Quite Claiming Causality with Julia Rohrer

Psychological research faces a critical transition as the field moves from traditional, recipe-based statistical methods toward more rigorous causal inference frameworks. Julia Rohrer, an academic at Leipzig University, highlights that while the open science movement has successfully shifted norms toward data sharing and transparency over the last 14 years, significant conceptual gaps remain. Researchers often rely on "checklist" statistics that mask underlying assumptions, leading to erroneous causal claims. Instead of hiding these assumptions behind boilerplate disclaimers, the field must prioritize explicit identification strategies and transparent modeling. This shift requires moving away from the pressure to produce "sexy" narratives and toward a culture where researchers acknowledge the limitations of their data. Ultimately, improving scientific credibility depends on fostering a research environment that values methodological honesty and the ability to distinguish between mere associations and genuine causal mechanisms.