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- Craig Anderson
Dr Craig Anderson
University of Technology Sydney
Craig Anderson graduated with an Honours degree in Statistics from the University of Glasgow, and then obtained his PhD in Statistics within the same department under the supervision of Dr Duncan Lee and Dr Nema Dean. The title of his thesis was "Identifying Boundaries in Spatial Modelling". After completing his PhD, he moved to Australia to take up a position as a Postdoctoral Research Fellow at the University of Technology Sydney, working with Professor Louise Ryan as part of the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS). Craig's main interests lie in statistics for health data; specifically spatial and spatio-temporal modelling of disease risk and the modelling of child growth trajectories.
Research Interests:
Biostatistics
Health
Spatial Epidemiology
Spatial statistics
Qualifications:
BSc (Hons) Statistics - University of Glasgow
PhD Statistics - University of Glasgow
Projects
Publications
Invited talks, refereed proceedings and other conference outputs
Anderson, C.
(2016). Spatio-temporal modelling of heart disease in New South Wales, Australia.
26th Annual Conference of The International Environmetrics Society.
Journal Articles
Anderson, C., Hafen R., Sofrygin O., Ryan L. M., & Community members. of the H. B. G.
(2019). Comparing predictive abilities of longitudinal child growth models.
Statistics in Medicine. 38(19), 3555 - 3570. doi: 10.1002/sim.7693
Huque, H., Anderson C., Walton R., Wolford S., & Ryan L. M.
(2018). Smooth individual level covariates adjustment in disease mapping.
Biometrical Journal. 60(3), 597-615. doi: 10.1002/bimj.201700143
Anderson, C., Lee D., & Dean N.
(2017). Spatial clustering of average risks and risk trends in Bayesian disease mapping.
Biometrical Journal. 59(1), 41-56. doi: 10.1002/bimj.201600018
Anderson, C., & Ryan L. M.
(2017). A Comparison of Spatio-Temporal Disease Mapping Approaches Including an Application to Ischaemic Heart Disease in New South Wales, Australia.
International Journal of Environmental Research and Public Health. 14(2), 146-162. doi: 10.3390/ijerph14020146
Anderson, C., Lee D., & Dean N.
(2016). Bayesian cluster detection via adjacency modelling.
Spatial and Spatio-temporal Epidemiology. 16, 11-20. doi: 10.1016/j.sste.2015.11.005
Huque, MH., Anderson C., Walton R., & Ryan L. M.
(2016). Individual level covariate adjusted conditional autoregressive (indiCAR) model for disease mapping.
International Journal of Health Geographics. 15(1), doi: 10.1186/s12942-016-0055-7
Research links
