About the speaker
I am a personality psychologist by training and my work covers a broad range of topics, including the effects of birth order, age patterns in personality, and the correlates and determinants of subjective well-being. My methodological interests include causal inference on the basis of observational data and data analytic flexibility. I am an active advocate for increased research transparency and have frequently given talks on the topic.
I recently finished my doctoral degree as a fellow of the International Max Planck Research School on the Life Course and am now a lecturer (Akademische Assistentin) at the Department of Psychology, University of Leipzig.
To learn more, go to https://juliarohrer.com/.
About the talk
Data analysis requires researchers to make many decisions — and sometimes, they may not know which choices are most appropriate. In this talk, I will give an overview of ways to tackle researcher degrees of freedom in a transparent manner (such as robustness checks, multiverse and specification curve analyses), highlight their commonalities, and discuss some crucial concerns.