Causation in Science

An introduction and update on developments in causal inference as applied to intervention effects.

Science is the discovery and measurement of reproducible effect, which is clouded by confounding bias. This seminar will introduce the idea of causal inference through a mechanistic approach using directed acyclic graphs (DAGs). Latest developments will be discussed regarding the causal inference approach to measuring intervention effects via multiple pathways on the outcome of interest. This seminar will be conceptual and no background to causal inference or DAGs are required.  

Speaker Bio:

Dr Mithilesh Dronavalli is Indian and has studied medicine, biostatistics and epidemiology at a postgraduate level. He has 4 years’ experience in public health and clinical research and 4 years’ experience in clinical psychiatry. He has a special interest in causal inference, Table Tennis and performing Indian Classical Music.