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    Letter to the Editor on detecting and dealing with heterogeneity in meta-analyses by Cordero and Dans

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    Authors
    Hoaglin, David C.
    UMass Chan Affiliations
    Division of Biostatistics and Health Services Research, Department of Population and Quantitative Health Sciences
    Document Type
    Letter to the Editor
    Publication Date
    2021-06-10
    Keywords
    Heterogeneity
    Q statistic
    I2
    Biostatistics
    Clinical Epidemiology
    Epidemiology
    Health Services Research
    
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    Link to Full Text
    https://doi.org/10.1016/j.jclinepi.2021.06.003
    Abstract
    Cordero and Dans give valuable advice on various aspects of detecting and dealing with heterogeneity in meta-analyses. For assessing statistical heterogeneity, they start with a forest plot of the study-level effect estimates and complement it with 2 related numerical measures, Q and I2. Other recommended approaches in the literature include the between-study standard deviation and a prediction interval for the effect in a new study. All these approaches have shortcomings, which investigation of heterogeneity should take into account. Surprisingly, the limitations of Q and I2, the 2 most popular, are not yet widely understood.
    Source

    Hoaglin DC. Letter to the Editor on detecting and dealing with heterogeneity in meta-analyses by Cordero and Dans. J Clin Epidemiol. 2021 Jun 10:S0895-4356(21)00181-5. doi: 10.1016/j.jclinepi.2021.06.003. Epub ahead of print. PMID: 34118366. Link to article on publisher's site

    DOI
    10.1016/j.jclinepi.2021.06.003
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/46954
    PubMed ID
    34118366
    Related Resources

    Link to Article in PubMed

    ae974a485f413a2113503eed53cd6c53
    10.1016/j.jclinepi.2021.06.003
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    Population and Quantitative Health Sciences Publications

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