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    Sensitivity of test for overdispersion in Poisson regression

    Access Status
    Fulltext not available
    Authors
    Xiang, Liming
    Lee, Andy
    Date
    2005
    Type
    Journal Article
    
    Metadata
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    Citation
    Xiang, Liming and Lee, Andy. 2005. Sensitivity of test for overdispersion in Poisson regression. Biometrical Journal 47 (2): 167-176.
    Source Title
    Biometrical Journal
    DOI
    10.1002/bimj.200310096
    Faculty
    School of Public Health
    Division of Health Sciences
    Remarks

    Copyright 2005 John Wiley & Sons, Ltd.

    Please refer to the publisher for the definitive published version.

    URI
    http://hdl.handle.net/20.500.11937/42652
    Collection
    • Curtin Research Publications
    Abstract

    Overdispersion or extra-Poisson variation is very common for count data. This phenomenon arises when the variability of the counts greatly exceeds the mean under the Poisson assumption, resulting in substantial bias for the parameter estimates. To detect whether count data are overdispersed in the Poisson regression setting, various tests have been proposed and among them, the score tests derived by Dean (1992) are popular and easy to implement. However, such tests can be sensitive to anomalous or extreme observations. In this paper, diagnostic measures are proposed for assessing the sensitivity of Dean's score test for overdispersion in Poisson regression. Applications to the well-known fabric faults and Ames salmonella assay data sets illustrate the usefulness of the diagnostics in analyzing overdispersed count data.

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