Slides from the CDC Cancer Conference (2003) course: Introduction
to Bayesian Mapping Methods
Downloadable Datasets:
Data sets from the book: Lawson, A. B. (2001) Statistical Methods in Spatial Epidemiology. Wiley, New York, can be downloaded here in Zip format
Mixture Model WinBugs code:
Download from here the WinBugs code for a two component relative risk mixture model in the class considered in Lawson and Clark (2002) Statistics in Medicine 21,359-370
Fortran and R code for a range of Disease Mapping Models
R/SPlus code
find the program code for a selection of disease mapping models: here
here find the program code for the Scottish lip cancer example
Fortran code
here find Fortran90 code for a range of simple mapping models:
BYM here
Marshall here
Gamma-Poisson (EB) here
MLwiN macros from the book Disease Mapping with WinBUGS and MLwiN
Macros used in this book relate to version 2.0 of MLwiN. Here find the downloadable macros
WinBUGS ODC files from the book Disease Mapping with WinBUGS and MLwiN
are available:
chapters 7 here chapter 8 here chapter 9 here
Corrected tables in chapter 8 for low birth weight example: here
Please note that due to confidentiality requirements no dataset is downloadable for the Weibull spatial analysis in chapter 9.
chapters 4 6 and 8: ODCs here, data (chapter 6 ) here data (chapter 8) here
WinBUGS ODC files and R code from the book Statistical Methods in Spatial Epidemiology 2nd ed
are available:
Appendix R code
WinBUGS code
WinBUGS ODC files and R code from the book Bayesian Disease Mapping: hierarchical modeling in spatial epidemiology
chapter3 chapter4 chapter5 chapter6 chapter7 chapter8 chapter9 chapter10 chapter11 AppendixA
Comment: are exceedence probabilities useful for detecting hot spots?
**new Elsevier JOURNAL: Spatial and Spatio-Temporal Epidemiology **
I am founding and chief editor for this new journal:
Aims and Scope
Spatial and Spatio-Temporal Epidemiology is a peer-reviewed scientific journal that provides a
home for high quality work which straddles the areas of GIS, epidemiology,
exposure science, and spatial statistics.
The journal focuses on answering
epidemiological questions where spatial and spatio-temporal approaches are
appropriate. The methods should help to advance our understanding of infectious
and non-infectious diseases in humans. The
journal will also consider applications where health care provision is the
focus. Coverage of veterinary topics will be included, and those with direct
human health implications are especially welcome. The journal places special emphasis on
spatio-temporal aspects of emerging diseases (e.g., avian flu, SARS),
development of spatial statistical and computational methods, and novel
applications of geospatial technology (e.g., GPS, GIS) for shedding insights on
exposure and disease processes.
The journal will accept two
different types of submissions: 1) methods papers that outline new methodology
in the areas of GIS, spatial statistics, exposure science, and/or epidemiology;
and 2) Case Study/Applications papers where recently developed methodology is
applied to novel applications with a clear exposure/disease focus.