Peter J. Diggle and Emanuele Giorgi

CHICAS, Lancaster University

Model-based geostatistics: geospatial statistical methods for public health applications

Course outline

• Course outline

Lecture material

• Overview
• Linear and logistic regression models
• Exploratory analysis
• Linear geostatistical models
• Geostatistical design
• Binomial geostatistical models
• Prevalence mapping
• Q&A, closing remarks

Lab material

• Introduction to R (slides and code)
• Introduction to R (code only)
• Introduction to R (solutions to exercises)
• Fitting linear and generalized linear models(slides and code)
• Fitting linear and generalized linear models(code only)
• Fitting linear and generalized linear models (solutions to exercises)
• Map-making in R (slides and code)
• Map-making in R (code only)
• Map-making in R (solutions to exercises)
• Linear geostatistical models (exercises and code)
• Linear geostatistical models (solutions to exercises)
• Geostatistical prediction (exercises and code)
• Geostatistical prediction(code only)
• Geostatistical prediction (solutions to exercises)
• Binomial geostatistical models (slides and code)
• Binomial geostatistical models(code only)
• Binomial geostatistical models (solutions to exercises)
• Prevalence mapping (slides and code)
• Prevalence mapping (code only)
• Prevalence mapping (solutions to exercises)

Getting started with R

• IntrotoRforMac
• IntrotoRforPC
• examplesession.R

More detailed notes on R

• For a more detailed set of notes by Bill Venables and David Smith, click here

  Data-sets

  • README.txt
  • cholera_explain.txt
  • cholera.deaths.txt
  • cholera.pumps.txt
  • Loaloa.explain.txt
  • Loaloa.txt
  • LiberiaRemoData.csv
  • LiberiaRemo_explain.txt
  • elevation.csv
  • elevation_explain.txt
  • lead2000.csv
  • lead2000_explain.txt
  • Galicia_boundary.csv

  Information on R packages

  • Introduction to the geoR package

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  http://www.lancs.ac.uk/staff/diggle/

  Last Modified: 27/10/2014