Sensitivity Analysis of Publication Bias in Meta-analysis : A Bayesian Approach

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著者

    • Ohashi Yasuo OHASHI Yasuo
    • Department of Biostatistics / Epidemiology and Preventive Health Sciences, School of Health Sciences and Nursing, University of Tokyo

抄録

Due to the selection process in academic publication, all meta-analysis of published literature is more or less affected by the so-called publication bias and tends to overestimate the effect of interest. Statistically, publication bias in meta-analysis is a selection bias which results from a non-random sampling from the population of unpublished studies. Several authors proposed methods of modelling publication bias using a selection model approach, which considers a joint modelling of the weight function representing the publication probability of each study and a regression of the outcome of interest. Copas (1999) showed that in this approach some of the model parameters are not estimable and a sensitivity analysis should be conducted. In implementing the Copas's sensitivity analysis of publication bias, a practical difficulty arises in determining the range of sensitivity parameters appropriately. We propose in this article a Bayesian hierarchical model which extends Copas's selectivity model and incorporates the experts' opinions as a prior distribution of sensitivity parameters. We illustrate this approach with an example of the passive smoking and lung cancer meta-analysis.

収録刊行物

  • 計量生物学  

    計量生物学 27(2), 109-119, 2006-12-01 

    The Biometric Society of Japan

参考文献:  19件

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各種コード

  • NII論文ID(NAID)
    10018385914
  • NII書誌ID(NCID)
    AA11591618
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    0918-4430
  • NDL 記事登録ID
    8596766
  • NDL 雑誌分類
    ZR1(科学技術--生物学)
  • NDL 請求記号
    Z74-B725
  • データ提供元
    CJP書誌  NDL  J-STAGE 
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