Researcher

Professor Jake Olivier

My Expertise

Biostatistics; Injury epidemiology; Road safety

Fields of Research (FoR)

Biostatistics, Applied statistics, Epidemiological methods, Injury prevention, Statistical data science

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Biography

I am part of the Biostatistics and Ecology research group in the School of Mathematics and Statistics. My research interests are focused on statistical methods applied to epidemiological, psychological and population health data. My main application area is in road safety and injury research, although I routinely collaborate with cancer, psychological and cardiovascular researchers.

Research Goals

I am part of the Biostatistics and Ecology research group in the School of Mathematics and Statistics. My research interests are focused on statistical methods applied to epidemiological, psychological and population health data. My main application area is in road safety and injury research, although I routinely collaborate with cancer, psychological and cardiovascular researchers.

Research Goals

  • Improving methods for assessing population-based interventions
  • Developing methods for estimating and accounting for regression to the mean
  • Novel methods for estimating population attributable fractions (with Dr Maarit Laaksonen)
  • Making sense of naturalistic driving study data

Research in Detail

There are many statistical challenges in quasi-experimental designs due to lack of randomisation. This makes it difficult to assess the impact of population-based interventions due to unmeasured confounding. Some examples of interest are assessing the effects of bicycle helmet legislation and measures to limit access to guns. Interrupted time series, with or without a control, offer an improvement over other methods. However, little work has been done in this area and there is little standardization of analytic approaches across various fields such that varying analyses can lead to disparate conclusions using the same data source.

It is well known that statistical significance is a function of sample size. This is problematic because important effects can go unnoticed in studies with small sample sizes, and unimportant effects can give small p-values from large studies. Effect sizes can complement significance testing by removing the influence of sample size. A lot of work on this topic can be found in psychological research but little has been done on epidemiological measures like the odds ratio, relative risk or hazards ratio.


My Grants

NHMRC MRFF Grant 2020 -- 2025, J. Pimanda, M. Polizzotto, M. Hertzberg, A. Wei, M. Dawson, R. Lock, A. Unnikrishnan, J. Olivier, C. Fong, P. Campbell, AZA+: A multi-site phase 1/2 dose escalation/expansion trial combining azacitidine and defactinib for high-risk myelodysplastic syndrome patients who fail to respond to azacitidine alone

Queensland Department of Transport and Main Roads 2019 -- 2020. J. Hatfield, S. Boufous, R. Friswell, J. Olivier, A. Williamson. Development and application of a young driver evaluation framework and toolset

ARC Discovery 2017 -- 2019, J. Brown, L. Bilston, J. Charlton, S. Koppel, L. Keay, J. Olivier, Design features critical for correct use of child car restraints

Transport for New South Wales 2017 -- 2018, T. Senserrick, S. Boufous, J. Hatfield, J. Olivier, A Williamson, GJ Knight, Evaluation of the NSW Motorcycle Graduated Licencing System

Swedish Transport Administration 2016 -- 2018, J. Olivier, R. Grzebieta, Systematic review of the impact of bicycle helmet use and legislation on cycling injury and participation

Queensland Department of Transport and Main Roads 2016 -- 2017, T. Senserrick, S. Boufous, J. Hatfield, J. Olivier, Queensland's Graduated Licensing System (GLS)


My Qualifications

Accredited Statistician (AStat), Statistical Society of Australia, 2016 - 

PhD in Statistics, University of Mississippi, 2003

MSc in Mathematics, University of Mississippi, 1997

BSc in Mathematics, Centenary College of Louisiana, 1995


My Awards

2 Web of Science Highly Cited Papers (1 in Mathematics, 1 in Social Sciences)

University of Mississippi Dissertation Fellowship 

John A. Hardin Mathematics Award, Centenary College

Paul and Myrtle Bender Mathematics and Physical Science Scholarship, Centenary College


My Research Supervision


Areas of supervision

Interrupted time series methods for assessing population-based interventions

Methods for regression to the mean

Joint modelling of longitudinal and time-to-event data


Currently supervising

Rianti Siswi Utami (with A/Prof Pierre Lafaye de Micheaux, Dr Maarit Laaksonen)

Raaj Kishore Biswas (with Em Prof Ann Williamson, Prof Teresa Senserrick)


My Engagement

Statistical Advisor, BMJ Open

Associate Editor, Journal of Road Safety

Editorial Board, ANZ Journal of Statistics

Editorial Board, Injury Prevention

Past President/VP and Treasurer of the NSW Branch of the Statistical Society of Australia, and past Chair of the Biostatistics Section

Member, American Statistical Association

Member, Australasian College of Road Safety

Member, Australian Injury Prevention Network


My Teaching

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Location

School of Mathematics and Statistics
Room 2051, The Red Centre (H13)
University of New South Wales
Sydney, NSW 2052

Map reference (Google map)

Contact

02 9385 6656