Dr Earl Duncan

Earl DuncanQualifications

PhD (Statistics), QUT.
B AppSc (Hons: Statistics), QUT.
B Math (Statistics), QUT.
B Bus (Accounting, International Business), QUT.

Research Interests

  • Spatial modelling (e.g. disease mapping)
  • Spatio-temporal modelling
  • Data visualisation (especially spatial visualisations, e.g. choropleth and other thematic maps, cartograms)
  • Bayesian estimation techniques (improvements to existing algorithms, ensemble algorithms)
  • Environmental statistics and sustainability

Recent and Current Projects

My most recent project was the development of the Australian Cancer Atlas.  The output is a publicly accessible , online, interactive map (think Google Earth) showing estimated incidence and relative survival rates for many different types of cancers across Australia at the small area level (SA2s).  This was joint work with the Cancer Council Queensland and the QUT Visualisation and eResearch (ViseR) team to combine our expertise in statistical spatial modelling, data visualisation, and UX and UI design. A screen-capture of the atlas is shown below.

BRAG Project - Atlas

For more information about the Australian Cancer Atlas, please visit the website: http://atlas.cancer.org.au/.

There are many extensions planned for the atlas, including:

  • Spatio-temporal modelling to see how patterns of a given cancer change over time.
  • Investigating different measures of survival (e.g. loss of life expectancy).
  • Ecological modelling (adding additional covariates based on area-specific socio-demographics or clinical characteristics).
  • Exploring relationships/clusters between cancers.
  • Adding new data sources including estimates for small-area variation in cancer screening.

There are also plans to develop a new spatial model and investigate the issue of over- and under-smoothing.  Earl is currently working on these research areas.

BRAG Presentations

Guides

  • Computing centroids of areas – bounding box vs centre of gravity methods: Coming soon

Publications

PhD Thesis:

Duncan, E. W.  2017.  Bayesian approaches to issues arising in spatial modelling.  PhD Thesis, Queensland University of Technology.  URL: https://eprints.qut.edu.au/112356/1/Earl_Duncan_Thesis.pdf.

Published (most recent first):

  1. Mengersen, K., E. Duncan, J. Arbel, C. Alston-Knox, and N. White.  2018.  “Chapter 15: Applications in Industry”.  In Handbook of Mixture Analysis, Handbooks of Modern Statistical Methods Series, edited by S. Früwirth-Schnatter, G. Celeux, and C. P. Robert.  Milton: Chapman & Hall/CRC.
  2. Cramb, S. M., E. W. Duncan, K. L. Mengersen, and P. D. Baade.  2018.  Australian Cancer Atlas, small-area incidence: technical report.  Brisbane: Cancer Council Queensland and Queensland University of Technology (QUT). (Not publicly available).
  3. Cramb, S. M., E. W. Duncan, K. L. Mengersen, and P. D. Baade.  2018.  Australian Cancer Atlas, small-area survival: technical report.  Brisbane: Cancer Council Queensland and Queensland University of Technology (QUT).  (Not publicly available).
  4. Cramb, S. M., E. W. Duncan, P. D. Baade, and K. L. Mengersen.  2018.  Investigation of Bayesian spatial models.  Brisbane: Cancer Council Queensland and Queensland University of Technology (QUT).  URL: https://eprints.qut.edu.au/115590.
  5. Duncan, E. W., N. M. White, and K. Mengersen.  2017.  Spatial smoothing in Bayesian models: a comparison of weights matrix specifications and their impact on inference.  International Journal of Health Geographics 16 (1): 47.  DOI: 10.1186/s12942-017-0120-x.
  6. Cramb, S. M., E. W. Duncan, N. M. White, P. D. Baade, and K. L. Mengersen.  2016. Spatial Modelling Methods. Brisbane: Cancer Council Queensland and Queensland University of Technology (QUT).
  7. Duncan, E. W., N. M. White, and K. Mengersen.  2016.  Bayesian spatiotemporal modelling for identifying unusual and unstable trends in mammography utilisation. BMJ Open 6 (5): p.e010253. DOI: 10.1136/bmjopen-2015-010253.
  8. Pokorny, M. R., M. de Rooij, E. Duncan, F. H. Schröder, R. Parkinson, J. O. Barentsz, and L. C. Thompson. 2014.  Prospective Study of Diagnostic Accuracy Comparing Prostate Cancer Detection by Transrectal Ultrasound–Guided Biopsy Versus Magnetic Resonance (MR) Imaging with Subsequent MR-guided Biopsy in Men Without Previous Prostate Biopsies. European Urology 66 (1): 22-29.  DOI: 10.1016/j.eururo.2014.03.002.

Under review/ in progress:

  1. Mengersen, K., E. Duncan, S. Cramb et al.  “A comparison of Bayesian spatial models for cancer incidence: theory and performance”.  In TBA, edited by K. Mengersen, TBA. Forthcoming 2019/2020.
  2. Duncan, E. W., S. M. Cramb, J. F. Aitken, K. L. Mengersen, and P. D. Baade.  The Australian cancer atlas.  Submitted to International Journal of Health Geographics, 18 April 2019.
  3. Jahan, F., E. Duncan, S. Cramb, P. Baade, and K. Mengersen.  Making more of disease maps: a Bayesian meta-analysis approach.  In preparation for submission to Statistical Methods in Medical Research.

Peer Review

 

Date Article Journal Status
July 2018 Risk Patterns of Lung Cancer Mortality in Northern Thailand BMC Public Health Published
Sep 2018 Evaluation of Bayesian Multiple Stage Estimation under Spatial CAR Model Variants Journal of Statistical Computation and Simulation Published
Jan 2019 A Comparison Study on Criteria to Select the Most Adequate Weighting Matrix Entropy Published
Mar 2019 Spatial pattern consistency among different remote-sensing land cover International Journal of Geo-Information Published
July 2019 Analysis of Spatial and Temporal Brickfield Development Patterns in the Peri-urban Area of Dhaka, Bangladesh International Journal of Geo-Information Under review

Contact Details

Email: earl.duncan@qut.edu.au

Other links:

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10 thoughts on “Dr Earl Duncan

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  6. Pingback: Congratulations Dr Earl Duncan and Dr Ben Fitzpatrick! | Bayesian Research & Applications Group

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