Quantitative social science for health and wellbeing research: the COMPASS Research Centre
April 4, 2019 - Presented by Dr Barry Milne and Dr Nichola Shackleton from The University of Auckland, hosted by THE UNIVERSITY OF QUEENSLAND
Date / Time
11:00 am 04/04/2019 -
12:30 pm 04/04/2019
Seminar 201, Level 2 - Cycad Building #1018, Long Pocket, The University of Queensland
UQ Long Pocket Campus, 80 Meiers Road, Indooroopilly QLD, Australia
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Dr Barry Milne and Dr Nichola Shackleton will describe the research programme of the Centre of Methods and Policy Application in the Social Sciences (COMPASS) at the University of Auckland. COMPASS uses quantitative methods to understand the drivers of health and wellbeing, often (but not exclusively) for children, and often (but not exclusively) by analysing whole population data. We will illustrate the work of COMPASS by describing four projects: a project using simulation to test policy scenarios for child outcomes; a project investigating loneliness across the life-course; a project assessing associations between child poverty and health outcomes; and a programme of research seeking to understand the key drivers of healthy weight, successful learning and literacy, and mental health resilience among children and young people.
Barry Milne is Director of the Centre of Methods and Policy Application in the Social Sciences (COMPASS) at the University of Auckland. He leads a team investigating the life-course development of health and social outcomes using the Integrated Data Infrastructure (IDI). His background is in lifecourse psychiatric epidemiology and has worked on a number of birth cohort studies, including the Dunedin Multidisciplinary Health and Development Study, the Twins Early Development Study (UK),and the Growing Up in New Zealand Study.
Nichola Shackleton is a Senior Research Fellow at COMPASS Research Centre at the University of Auckland. She is a social scientists specialising in quantitative research methods and social statistics. Her research interests include measuring and reducing inequalities in child and adolescent health, longitudinal data analysis, and latent variable modelling.