A journey in causal inference: from complicated algebra to a simple unifying approach

Thursday, 15 March 2018
Monash University, School of Public Health & Preventive Medicine
553 St Kilda Rd (Conference Rooms 1 & 2, Ground Floor)

In 2003 I presented a Melbourne biostatistics seminar on an application of a newly emerging method – marginal structural modelling – to address time-varying confounding in observational studies of the effect of health care interventions. Penetrating questions revealed deficiencies in my understanding of the approach. I will describe attempts to improve my understanding of methods to make causal inferences from observational data over the subsequent 15 years, and the corresponding change in emphasis from difficult algebra to a simpler unifying approach.


Professor Jonathan Sterne

Prof. Jonathan Sterne

Department of Population Health Sciences
University of Bristol

Jonathan Sterne is Professor of Medical Statistics and Epidemiology in the University of Bristol’s Department of Population Health Sciences, and Deputy Director of the NIHR Bristol Biomedical Research Centre. Jonathan has a longstanding interest in methods for systematic reviews and meta-analysis, led development of the ROBINS-I tool for assessing risk of bias in non-randomised studies of interventions, and contributed to the development of the Cochrane risk of bias tool for randomised trials. He also leads a large collaboration of HIV cohort studies that led to advances in our understanding of prognosis of HIV-positive people in the era of effective antiretroviral therapy. He has authored highly-cited papers on causal inference, including methods for instrumental variable analyses of Mendelian randomisation studies. Other research interests include methodology for epidemiology and health services research and the epidemiology of asthma and allergic diseases.