- Methods for smoothing of direct estimates in time and space, and mapping the subsequent estimated are contained in the SUMMER package at CRAN: SUMMER
- GitHub version of SUMMER (contains latest version): GitHub SUMMER
- Shiny App for SUMMER: SUMMER Shiny App
- ShinyApp for TMB/INLA comparison: Shiny App for TMB/INLA Simulations TMB/INLA paper: here.
- TMB Code: here. TMB/INLA paper: here.
- Files to accompany Wakefield, Fuglstad, Riebler, Godwin, Wilson and Clark, "Estimating Under 5 Mortality in Space and Time in a Developing World Context". Paper: here. Supplementary Materials: here. Software will be here soon.
- Reference: Chen, Wakefield and Lumley "The use of sample weights in Bayesian spatial hierarchical models for small area estimation" is here.
- Code to implement the simulation in Wakefield, Simpson and Godwin is here.

- Details of R package SpatialEpi to perform various methods in Spatial Epidemiology can be found here SpatialEpi
- WinBUGS code for models fitted in Bauer and Wakefield "Stratified space-time infectious disease modeling: with application to hand, foot and mouth disease in China" is here.

- Excel spreadsheet for calculating approximate Bayes factors for genetic epidemiology studies here ; R code is here and here (the latter for combining two studies also). Example is here

The paper "A Bayesian Measure of the Probability of False Discovery in Genetic Epidemiology Studies" is on the publications page. - Details of R package to evaluate methods described in Biometrics paper (paper is here) can be found at HWEBAYES

WinBUGS code for examining Hardy-Weinberg Equilibrium here. R script to run the four allele example from the Biometrics paper here. Short user-manual for this example: here.

- Bayes Analysis of Two-Phase Data: Random Sampling Code is here and example is here. Bayes Analysis of Two-Phase Data: Case-Control Sampling Code is here and example is here. Accompanying paper is to appear in Biometrics. Code was written by Michelle Ross.
- The R Code to carry out two-phase sampling in an ecological setting as descibed in "Overcoming ecological bias using the two-phase study design" by Wakefield and Haneuse, American Journal of Epidemiology (see publications page for more details) is here, and requires the R functions tps.q - the latter is an R version of th e Splus code written by Norm Breslow and Nilanjan Chatterjee. The code works with the North Carolina data infantsAgg.dat.

- Bayesian population PK/PD modeling developed for BUGS by me, Dave Lunn, Nicky Best and Dave Spiegelhalter: PKBUGS
- Bugs code for Zhou and Wakefield (2006, Biometrics) paper on curve clustering here