Description

Due to ethical or practical reasons, observational studies are often used in public health. While we are often interested in causal effects (to guide interventions and policy), many of these observational studies rely on associational rather than causal analysis. This may result in the observed associations being spurious because of different types of biases (e.g., confounding bias). Causal inference methods help researchers better understand under what conditions a causal effect can be identified and how to conduct observational and quasi-experimental studies to answer causal questions.

This seminar will be led by Dr. Julia Rohrer from Leipzig University (https://juliarohrer.com/). Dr. Rohrer, a psychologist, is renowned for her expertise in introducing causal inference methods for observational research. Her 2018 paper, "Thinking Clearly About Causation and Correlation," has been cited over 1,000 times. Dr. Louise Poppe from our department will present practical applications of these methods.