Factors Influencing Soay Sheep Survival: A Bayesian Analysis

Ruth King, SP Brooks, BJT Morgan, T Coulson

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

Abstract

This article presents a Bayesian analysis of mark-recapture-recovery data on Soay sheep. A reversible jump Markov chain Monte Carlo technique is used to determine age classes of common survival, and to model the survival probabilities in those classes using logistic regression. This involves environmental and individual covariates, as well as random effects. Auxiliary variables are used to impute missing covariates measured on individual sheep. The Bayesian approach suggests different models from those previously obtained using classical statistical methods. Following model averaging, features that were not previously detected, and which are of ecological importance, are identified.

Original languageEnglish
Pages (from-to)211-220
Number of pages10
JournalBiometrics
Volume62
Issue number1
DOIs
Publication statusPublished - Mar 2006

Keywords

  • age classes
  • annual survival
  • auxiliary variables
  • Bayesian p-values
  • goodness of fit
  • logistic regression
  • mark-recapture-recovery
  • model averaging
  • North Atlantic Oscillation
  • random effects
  • reversible jump Markov chain Monte Carlo
  • senescence
  • soay sheep
  • trans-dimensional simulated annealing
  • INTEGRATED RECOVERY/RECAPTURE DATA
  • MODEL SELECTION
  • AGE
  • SEX

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