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Design and analysis of clustered, unmatched resource selection studies


  • Robert G. Clark
  • Tanya C. Strevens


Studies which measure animals' positions over time are a vital tool in understanding the process of resource selection by animals. By comparing a sample of locations that are used by animals with a sample of available points, the types of locations that are preferred by animals can be analysed by using logistic regression. Random-effects logistic regression has been proposed to deal with the repeated measurements that are observed for each animal, but we find that this is not feasible in studies where the sample of available points cannot readily be matched to specific animals. Instead, we investigate the use of marginal logistic models with robust variance estimators, by using a study of Australian bush rats as a case-study. Simulation is used to check the properties of the approach and to explore alternative designs. Copyright (c) 2008 Royal Statistical Society.

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  • Robert G. Clark & Tanya C. Strevens, 2008. "Design and analysis of clustered, unmatched resource selection studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(5), pages 535-551.
  • Handle: RePEc:bla:jorssc:v:57:y:2008:i:5:p:535-551

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    References listed on IDEAS

    1. Lumley, Thomas, 2004. "Analysis of Complex Survey Samples," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 9(i08).
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