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A guide to Bayesian model checking for ecologists
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2018
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Source: Ecological Monographs, 88(4), 526-542
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Journal Title:Ecological Monographs
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Description:Checking that models adequately represent data is an essential component of applied sta- tistical inference. Ecologists increasingly use hierarchical Bayesian statistical models in their research.The appeal of this modeling paradigm is undeniable, as researchers can build and fit models that embody complex ecological processes while simultaneously accounting for observation error. However, ecologists tend to be less focused on checking model assumptions and assessing potential lack of fitwhen applying Bayesian methods than when applying more traditional modes of inference such as maxi-mum likelihood. There are also multiple ways of assessing the fit of Bayesian models, each of which has strengths and weaknesses. For instance, Bayesian Pvalues are relatively easy to compute, but are well known to be conservative, producing Pvalues biased toward 0.5. Alternatively, lesser known approaches to model checking, such as prior predictive checks, cross-validation probability integral transforms, and
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Source:Ecological Monographs, 88(4), 526-542
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ISSN:0012-9615
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Rights Information:CC0 Public Domain
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Rights Statement:This article is a U.S. Government work and is in the public domain in the USA.
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