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dc.date.accessioned2015-02-11T22:39:14Z
dc.date.available2015-02-11T22:39:14Z
dc.date.issued2014-03
dc.identifier.citationChambert, T., J.J. Rotella, and M.D. Higgs. 2014. Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates. Ecology & Evolution 4(8) :1389-1397. http://dx.doi.org/10.1002/ece3.993en_US
dc.identifier.issn2045-7758
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/8831
dc.description.abstractThe investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark–recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark–recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest.en_US
dc.subjectEcologyen_US
dc.titleUse of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital ratesen_US
dc.typeArticleen_US
mus.citation.extentfirstpage1389en_US
mus.citation.extentlastpage1397en_US
mus.citation.issue8en_US
mus.citation.journaltitleEcology & Evolutionen_US
mus.citation.volume4en_US
mus.identifier.categoryLife Sciences & Earth Sciencesen_US
mus.identifier.doi10.1002/ece3.993en_US
mus.relation.collegeCollege of Letters & Scienceen_US
mus.relation.collegeCollege of Letters & Science
mus.relation.departmentEcology.en_US
mus.relation.universityMontana State University - Bozemanen_US


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