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
  • Bayesian mixture models and development of relabelling algorithms to reverse label switching
  • Environmental statistics and sustainability

Current Projects

My current project is the development of an Australian national cancer atlas.  The end result will be a publicly accessible , online, interactive map (think Google Earth) showing estimated standardised incidence ratio and survival rates for many different types of cancers.  I work with 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.  My main contribution is the development of a new spatial model designed to avoid the issues of over- and under-smoothing, compare this model against other published methods using simulated data, and apply the model to real incidence and survival data which will be displayed in the cancer atlas.  Other contributions include finding the best (or at least good) ways to represent uncertainty around estimates.

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:

  1. 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.
  2. 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.
  3. 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).
  4. 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.
  5. 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:

  1. Mengersen, K., E. W. Duncan, N. M. White, J. Arbel, and C. Alston-Knox.  “Applications in Industry”.  In Handbook of Mixture Analysis, edited by G. Celeux, S. Früwirth-Schnatter, and C. P. Robert.  Chapman & Hall/CRC Handbooks of Modern Statistical Methods.  Forthcoming July 2018.
  2. Duncan, E. W., N. M. White, and K. Mengersen. Improved Bayesian methods for identifying aberrant temporal trends in spatio-temporal data with application to mammography screening services.  Submitted to PLOS ONE, May 2017.

Contact Details:

earl.duncan@qut.edu.au

 

 

 

Advertisements

4 thoughts on “Dr Earl Duncan

  1. Pingback: Brag Meeting 14th May 2015 | Bayesian Research & Applications Group

  2. Pingback: Brag Meeting 28th May 2015 | Bayesian Research & Applications Group

  3. Pingback: Brag Meeting 20th July 2017 | Bayesian Research & Applications Group

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

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s