Slides from the CDC Cancer Conference (2003) course:
Introduction
to Bayesian Mapping Methods
Slides from the NCI Geospacial Conference 2016
Here
Slides from the Plenary Talk at Environmetrics Edinburgh Conference 2016
Here
Slides from Keynote Address at the Spatial Statistics Conference Lancaster July 2017
Here
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
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
ODC files and R code from the 3rd Edition
Here and
Here
A recent Github repository of code for Nimble, BUGS, CARBayes and INLA can be found
Here
Code files from Using R for Bayesian Spatial and Spatio-Temporal Health Modeling
Here
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.