Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates

The 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...

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Published in:Ecology and Evolution
Format: Article in Journal/Newspaper
Language:unknown
Published: 2014
Subjects:
Online Access:https://scholarworks.montana.edu/xmlui/handle/1/8831
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spelling ftmontanastateu:oai:scholarworks.montana.edu:1/8831 2023-05-15T18:43:24+02:00 Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates 2014-03 application/pdf https://scholarworks.montana.edu/xmlui/handle/1/8831 unknown Chambert, 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/ece3.993 2045-7758 https://scholarworks.montana.edu/xmlui/handle/1/8831 Ecology Article 2014 ftmontanastateu 2022-06-06T07:27:15Z The 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. Article in Journal/Newspaper Weddell Seals Montana State University (MSU): ScholarWorks Weddell Ecology and Evolution 4 8 1389 1397
institution Open Polar
collection Montana State University (MSU): ScholarWorks
op_collection_id ftmontanastateu
language unknown
topic Ecology
spellingShingle Ecology
Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates
topic_facet Ecology
description The 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.
format Article in Journal/Newspaper
title Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates
title_short Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates
title_full Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates
title_fullStr Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates
title_full_unstemmed Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates
title_sort use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates
publishDate 2014
url https://scholarworks.montana.edu/xmlui/handle/1/8831
geographic Weddell
geographic_facet Weddell
genre Weddell Seals
genre_facet Weddell Seals
op_relation Chambert, 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/ece3.993
2045-7758
https://scholarworks.montana.edu/xmlui/handle/1/8831
container_title Ecology and Evolution
container_volume 4
container_issue 8
container_start_page 1389
op_container_end_page 1397
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