Blog
25.03.2025

Data Science Brown Bag: The Power of Causality: Julia Rohrer’s Research on Personality and Methodology

The latest session of the Brown Bag series featured an engaging talk by Julia Rohrer from the Wilhelm Wundt Institute for Psychology at the University of Leipzig. Her presentation, titled "Everything is Causal Inference!", explored the role of causal reasoning in research and why mastering it is essential for drawing meaningful conclusions from data.

Julia is committed to encouraging researchers to take causal inference seriously, believe in their ability to apply it correctly, and strive for better research practices that can inform decision-making more effectively.

Originally, her focus was on personality research, but the replication crisis brought widespread concerns about research quality. As someone working in a field that relies heavily on observational data, she identified an even greater problem: many researchers do not analyse their data correctly. This results in wasted research and studies that lack clear interpretation. Recognising the significance of this issue, Julia decided to make it her primary area of focus.

What Shapes Us? Insights from Personality Research

"My substantive research focuses on personality development, particularly whether and how our siblings influence who we become in adulthood," Julia explained. "It turns out that the effects of birth rank – whether you're a firstborn or later born – or sibling gender – whether you grow up with a sister or a brother – are very limited and inconsistent."

Despite these findings, her talk was about how we determine causation in research. Julia highlighted a crucial issue: "We've all been taught that correlation does not imply causation. Yet researchers rarely receive proper training on what to do next. This leaves many ill-equipped to navigate the complex causal inference challenges that arise in all types of research."

A Thought-Provoking Discussion

The event concluded with an engaging discussion where participants explored the real-world implications of causal inference and the challenges of drawing robust conclusions from observational data. Julia’s talk served as a reminder that causality underpins all research, making it a skill every researcher must master.