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A Comparison of GLM, GEE, and GLMM Applied to Badger Activity Data

  • N.J. Walker
  • A.F. Zuur
  • A. Ward
  • A.A. Saveliev
  • E.N. Ieno
  • G.M. Smith
Chapter
Part of the Statistics for Biology and Health book series (SBH)

Abstract

In this chapter, we analyse a data set consisting of signs of badger (Meles meles; see Fig. 22.1) activity around farms. The data are longitudinal and from multiple farms; so it is likely a temporal correlation structure is required. The response variable is binary; the presence or absence of badger activity. The dataset comes from a survey carried out on 36 farms over 8 consecutive seasons running from autumn 2003 to summer 2005. For analytical convenience, we consider these intervals to be exactly equal, which is a close enough approximation to the reality. All farms in the survey were in South-West England, which is a high-density badger country.

Keywords

Generalise Linear Modelling Generalise Linear Mixed Model Generalise Estimate Equation Generalise Estimate Equation Model Generalise Linear Modelling Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • N.J. Walker
    • 1
  • A.F. Zuur
    • 2
  • A. Ward
    • 3
  • A.A. Saveliev
    • 4
  • E.N. Ieno
    • 2
  • G.M. Smith
    • 5
  1. 1.Woodchester Park CSL, Tinkley Lane, NympsfieldGloucesterUK
  2. 2.Highland Statistics LTD.NewburghUK
  3. 3.Central Science Laboratory, Sand HuttonYorkUK
  4. 4.Faculty of EcologyKazan State UniversityKazanRussia
  5. 5.School of Science and EnvironmentBath Spa UniversityBathUK

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