Division of Biostatistics & Epidemiology
Data & Programs
Slides from the CDC Cancer Conference (2003) course: Introduction to Bayesian Mapping Methods
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
find the program code for the Scottish lip cancer example here
here find Fortran90 code for a range of simple mapping models:
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
Please note that due to confidentiality requirements no dataset is downloadable for the Weibull spatial analysis in chapter 9.
Data for chapter 8 here
WinBUGS ODC files and R code from the book Statistical Methods in Spatial Epidemiology 2nd ed
Appendix R code
WinBUGS ODC files and R code from the book Bayesian Disease Mapping: hierarchical modeling in spatial epidemiology
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.
Journal Website: http://www.ees.elsevier.com/sste/