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Dr Sophie Zaloumis graduated from The University of Melbourne in 2005 with a Bachelor of Science (Hons) degree in Statistics. In 2006 she began working as a Research Assistant (RA) in the Department of Physiology at The University of Melbourne. Her work in the Physiology Department involved using statistical models, that reflect genetic theory, to examine whether the variation in cardiovascular disease (CD) risk factors (such as blood pressure) are mainly due to differences between our DNA base sequences or to environmental factors. The statistical models used to perform such analyses change depending on what scale (numerical or categorical) the risk factors are measured on.
Statistical models to analyse biological traits measured on categorical scales are not as well developed as those for continuous measurements in genetic epidemiology and in 2007 she started her PhD in the Physiology Department to address this gap in the methodology. She completed her PhD in 2011 and the result of my work was a non-proportional odds multivariate logistic regression model for correlated outcomes measured on ordinal scales and a Markov chain Monte Carlo algorithm to fit the model.
She started her position as a Biostatistician at the Centre for MEGA Epidemiology in 2010. Her research at the centre involves validating a within-host model of the dynamics of malaria parasites in the presence of antimalarial drug treatment and analysing data from the HealthIron study, which examines genetic and environmental modifiers of hereditary haemochromatosis (iron overload disease).
Monte Carlo algorithm, Biostatistics, Statistical models, Physiology
Kris M Jamsen, Sophie G Zaloumis, Katrina J Scurrah and Lyle C Gurrin
Research Article: J Biom Biostat 2012, S1-003