The Victorian Centre for Biostatistics
The Victorian Centre for Biostatistics (ViCBiostat) is a Centre of Research Excellence in biostatistics, led by researchers at the Murdoch Childrens Research Institute, Monash University and The University of Melbourne.
Biostatistics is a discipline of great importance to modern health research, encompassing the vital methods needed to design sound health research studies and lead the analysis and interpretation of data arising from such studies. In the modern era health research is data-intensive and statistical expertise is critical to understanding the growing volume of data being collected. However, the discipline of biostatistics is relatively underdeveloped in Australia, lacking major centres of sufficient critical mass to enable the development of methodological research programs and career paths for young statisticians.
ViCBiostat was established in 2012 by a Centre of Research Excellence grant from the National Health & Medical Research Council (NHMRC), with funding for five years. The team’s focus is on methodological research and high-level training of professional biostatisticians, within a framework that emphasises active collaboration and translation with the ultimate aim of improving the population’s health through high-quality research.
At the Murdoch Childrens Research Institute, ViCBiostat is embedded within CEBU and the Data Science Core, which provide essential input to a wide range of research projects and groups at the Melbourne Children’s campus. Biostatisticians are centrally involved in key research programs affecting the health of children, for example those with cystic fibrosis, cardiac anomalies, developmental disorders, lung disease and many others, as well as healthy children followed up with a view to learning about prevention of later ill-health.
For more information about ViCBiostat and an outline of the research on which we are working see www.vicbiostat.org.au.
The Centre is led by Professor John Carlin who heads the Clinical Epidemiology and Biostatistics Unit at the Murdoch Childrens Research Institute and also holds appointments with The University of Melbourne. Since completing his PhD in statistics at Harvard University he has been involved in a wide range of medical and public health research, including clinical trials and large-scale epidemiological studies, as well as research on methods for longitudinal analysis and handling incomplete data.
Principal collaborators are:
Professor Andrew Forbes
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) he has been actively engaged in collaborative epidemiological and clinical research projects. His research interests are methods for comparative effectiveness research, assessment of the effects of time dependent exposures, interrupted time series designs and methodology in clinical trials.
Associate Professor Lyle Gurrin
Biostatistical researcher with the Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, University of Melbourne. He completed a PhD in statistics at the Telethon Institute for Child Health Research in Perth and is the principal investigator of the HealthIron cohort study and chief investigator on projects in asthma, allergy and immunology. His methodological research interest are in methods for longitudinal data and causal analysis in cohort studies.
Associate Professor Julie Simpson
Heads the Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, University of Melbourne. She completed her postgraduate training in statistics at the University of Cambridge and Open University, UK, and is actively engaged with the international community in population health research. Her research interests include nonlinear mixed-effects modelling in pharmacokinetic-pharmacodynamic studies and methods for handling missing data in longitudinal cohort studies.
Professor Rory Wolfe
Professor Rory Wolfe is a biostatistician at Monash University and contributes to a wide range of epidemiological and clinical research studies. He obtained his PhD in statistics from Southampton University (UK), subsequently did research in statistical methodology for longitudinal studies, and maintains methodological interests in missing data in risk prediction models, joint modelling of mortality and cognitive decline, and applications of propensity scoring methods.
For more of the people involved in ViCBiostat, see www.vicbiostat.org.au/people.
ViCBiostat research program
Our research is guided by the concept of a “methodological and translational pipeline”. Applied biostatistical research is required at multiple levels in order to enable the fruitful application of new statistical methods in health and medical research studies: (i) new methodology needs to be developed with appropriate mathematical understanding and a capacity to tailor general ideas to suit practical application; (ii) methods need to be assessed analytically or by numerical simulation in realistic practical scenarios; (iii) methods need to be translated into more accessible language and software to enable broad use by the practising applied biostatistician or data analyst working in government, industry or university departments; and (iv) awareness of the value (and limitations) of new methodology needs to be promulgated widely to the broader research community in order to enable its acceptance and application in health/medical research studies that will inform health policy or practice.
Details of some of our specific research programs can be found at www.vicbiostat.org.au/research-projects.
Beyond our core research program, we develop training programs in biostatistical methods, including specialist PhD training as well as workshops and courses for epidemiologists and other health researchers. The Centre aims to play an active role in the dissemination of sound statistical methods throughout the health research sector. Its translation activities include a wide range of substantive collaborations in which the biostatistical contribution is critical, and extend beyond that to direct contributions to health policy and health services decision-making.