25 Feb 2020 09:00am to 28 Feb 2020 05:00pm

ViCBiostat Summer School 2020

Event Location
Conference Room 1
553 St Kilda Road Melbourne Australia
Melbourne VIC 3004
Dr Lorenzo Trippa
Department of Biostatistics, Harvard T.H. Chan School of Public Health
Dr Steffen Ventz 
Harvard T.H. Chan School of Public Health
Prof John Carlin
John holds appointments with the Murdoch Children’s Research Institute and The University of Melbourne. Since completing a PhD in Statistics at Harvard University he has been engaged as a collaborator...
Margarita Moreno Betancur
Margarita is co-lead of the Clinical Epidemiology and Biostatistics Unit (CEBU) at the MCRI and the University of Melbourne. Since completing her PhD in Biostatistics at Université Paris-Sud in 2014...
Andrew is the current Head of the Biostatistics Unit in the Department of Epidemiology and Preventive Medicine at Monash University. Since completing a PhD in Statistics at Cornell University (USA)...
Lyle Gurrin is Professor of Biostatistics at the Centre for Epidemiology and Biostatistics at the Melbourne School of Population and Global Health, and President of the Victorian Branch of the...

The Victorian Centre for Biostatistics (ViCBiostat) will offer two exciting new courses in the 2020 edition of its Summer School.


25-26 Feb: Causal Inference in Health Data Science

In this era of “data science” it is vitally important to clearly articulate the questions that we ask of data, understand the challenges inherent in answering different types of questions, and ensure that our analysis methods are suitably aligned. An overwhelming number of clinical and public health research studies ask “causal” questions, for example about the effect of treatments, policies, behaviours and other exposures on health outcomes. Causal inference requires carefully structured reasoning to guide appropriate statistical analysis.

This course will provide a comprehensive introduction to causal thinking and the key methods for defining and estimating causal effects. Presenters will be our own internationally recognised researchers in this area of methodology, led by Dr Margarita Moreno-Betancur, and including Prof Andrew Forbes, Prof John Carlin and Prof Lyle Gurrin.


27-28 Feb: Bayesian Adaptive Randomized Clinical Trials (in conjunction with the Australian Clinical Trials Alliance)

Adaptive clinical trial designs have proven valuable to accelerate the development of new treatments. Adaptive randomization based on Bayesian principles has been proposed for testing several treatments in complex clinical trials on heterogeneous populations. Recent applications suggest that outcome-adaptive approaches can accelerate drug development processes. Adaptive algorithms attempt to learn and identify, during the trial, the best available treatment options for individual patients enrolled in the trial.

This workshop will be delivered by two international leaders in this field, Dr Lorenzo Trippa (Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, and Department of Biostatistics, Harvard T.H. Chan School of Public Health) and Dr Steffen Ventz (Department of Data Sciences and the Center for Regulatory Sciences at the Dana-Farber Cancer Institute and Department of Biostatistics, Harvard T.H. Chan School of Public Health).