Data & Programs

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

here

WinBUGS code

here

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?

here

**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/