Developing a Cancer Atlas using Bayesian Methods: A Practical Guide for Application and Interpretation
Revised June, 2024 (online v2.0)
Preface
Suggested Citation
Duncan, E. W., S. M. Cramb, P. D. Baade, K. L. Mengersen, T. Saunders, and J. F. Aitken. 2024. Developing a Cancer Atlas using Bayesian Methods: A Practical Guide for Application and Interpretation, 2nd ed. Brisbane: Queensland University of Technology (QUT) and Cancer Council Queensland.
List of Acronyms and Abbreviations
ABS | Australian Bureau of Statistics |
ACA | Australian Cancer Atlas |
BIC | Bayesian information criterion |
BYM | a model named after the authors Besag, York, and Molli\'e |
CAR | conditional autoregressive |
CI | credible interval |
CRAN | Comprehensive R Archive Network |
DAG | directed acyclic graph |
DCO | death certificate only |
DIC | deviance information criterion |
EHR | excess hazard ratio |
ERP | estimated residential population |
ESS | effective sample size |
GLM | generalised linear model |
i.i.d. | independent and identically distributed |
ICAR | intrinsic conditional autoregressive [model] |
INLA | integrated nested Laplace approximation |
IRSAD | index of relative socioeconomic advantage and disadvantage |
LPPD | log pointwise predictive density |
MCMC | Markov chain Monte Carlo |
PPD | posterior probability difference |
SA2 | statistical area level 2 |
SIR | standardised incidence ratio |
SLA | statistical local area |
SRE | spatial random effect |
WAIC | Watanabe-Akaike (or widely applicable) information criterion |
WSSP | weighted sum of spatial priors |
Acknowledgements
The authors would like to thank the many members of the Australian Cancer Atlas project team who contributed to this eBook, and the advice provided by the Project Advisory Team. We also appreciated the support of the individual state- and territory-based cancer registries, the Australasian Association of Cancer Registries, and Cancer Council Australia for this project. We acknowledge the expertise provided by the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS)
The authors would also like to thank Jess Cameron, a Research Fellow at Cancer Council Queensland, for proofreading and providing feedback on earlier versions of this eBook
Changes to this Edition
The changes to the previous edition (v1.0.1) are as follows:
- Use of simple features (
sf
) objects rather than the olderSpatialPolygons
andSpatialPolygonsDataFrame
objects. Thesf
package replaces thergeos
,rgdal
, andmaptools
packages which were deprecated at the end of 2023. The modern simple features make working with spatially indexed data much easier, both in terms of data manipulation and data visualisation. As a result, the R code used to produce maps has been greatly simplified. - The shapefile in Chapter 7 has been updated to ASGS 2021.
- An alternative way to obtain the spatial data via the
absmapsdata
package is provided.
- An alternative way to obtain the spatial data via the
- R code has been revised to make greater use of
dplyr
functions and piping. - All WinBUGS examples (Chapter 8, Section 9.9.5, and Appendix A.3) have been updated to OpenBUGS.
- Added details of the colour specifications and scales for the final version of the legend used in the Australian Cancer Atlas in Section 11.3.4.
- Fixed broken URLs due to link rot.
- Minor changes to the text to address typographical errors and to reflect changes to the code.
Contact
This eBook is maintained by the authors and may be updated periodically to add new content or make corrections. If you notice any errors, particularly with the code, or have any general enquiries, please contact the first author at earl.w.duncan@gmail.com.