The Health Economics team at the University of Sydney School of Public Health are looking to recruit a (junior) biostatistician to assist in undertaking research quantifying the association between healthcare costs, weight status, and culturally and linguistically diverse (CALD) groups in children. The biostatistician will analyse data from the Longitudinal Study of Australian Children (LSAC), a population-based, nationally representative longitudinal study of over 10,000 children, with over 15 years of follow-up.  

Each individual child enrolled in the LSAC is administratively linked to individual level healthcare costs, which include both the Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) records. This enables the analysis of healthcare costs associated with accessing medical services and prescription medications. Statistical models accounting for the longitudinal nature of the data and the right-skewed distribution in healthcare cost data will be used (such as generalised linear models, GEE, or two-part models). The dependent variable of interest will be annual healthcare costs, with predictors of cost (age, sex, socioeconomic status, ethnicity, Aboriginal and Torres Strait Islander status, weight status) included in the analysis. Interaction terms between Aboriginality and weight status, and CALD groups and weight status, will determine whether the weight status and healthcare cost relationship are modified by these demographic variables.

An understanding of longitudinal data and analysis and use of the statistical package Stata is essential. Individuals with an understanding of working with linked data would be viewed favourably however it is not essential. 

The candidate will work closely with Associate Professor Tom Lung and Professor Alison Hayes to conduct the analysis. The role is approximately 0.3 FTE (1.5 days) part time to the end of the year, however there is scope for flexibility (e.g., completing a larger workload in a shorter time frame). This represents an exciting opportunity to gain practical experience working with real data on an exciting and important project that may lead to more collaboration in the future. 

If you are interested, please contact Tom directly by email: tom.lung@sydney.edu.au