A comparison of the hierarchical likelihood and Bayesian approaches to spatial epidemiological modelling

MJ Jang, Y Lee, AB Lawson, WJ Browne

    Research output: Contribution to journalArticle (Academic Journal)peer-review

    9 Citations (Scopus)

    Abstract

    Recently Bayesian methods have been widely used in disease mapping. Hierarchical (h-) likelihood methods allow reliable likelihood inference in random-effect models and it is therefore interesting to compare h-likelihood and Bayesian methods. For comparison we consider three examples: low birth weight and cancer mortality data in South Carolina and lip cancer data in Scotland. Mean estimates from both h-likelihood and Bayesian approaches are almost identical, while variance-component estimates can be somewhat different, depending upon choice of priors.
    Translated title of the contributionA comparison of the hierarchical likelihood and Bayesian approaches to spatial epidemiological modelling
    Original languageEnglish
    Pages (from-to)809 - 821
    Number of pages13
    JournalEnvironmetrics
    Volume18 (7)
    DOIs
    Publication statusPublished - Nov 2007

    Bibliographical note

    Publisher: Wiley

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