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Modelling reporting bias: the operative mortality rate for ruptured abdominal aortic aneurysm repair

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  • Dan Jackson
  • John Copas
  • Alex J. Sutton

Abstract

Summary. It is perhaps underappreciated that ruptured abdominal aortic aneurysm is a significant cause of mortality in the UK. The only curative treatment is an emergency operation and quantifying the success of this presents many difficulties. In particular, there is empirical evidence of reporting bias, suggesting that studies failing to report operating theatre mortality may be those where death in theatre is more common. We suggest a procedure for correcting for this bias and re‐examine a recent meta‐analysis of the available data. This casts considerable doubt on some conclusions from naïve analyses that do not take into account the potential bias. Perhaps most importantly, our procedure indicates a modest improvement in operating theatre mortality over the last 50 years, which is a trend that is not evident from the usual naïve analyses.

Suggested Citation

  • Dan Jackson & John Copas & Alex J. Sutton, 2005. "Modelling reporting bias: the operative mortality rate for ruptured abdominal aortic aneurysm repair," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(4), pages 737-752, November.
    • Handle: RePEc:bla:jorssa:v:168:y:2005:i:4:p:737-752
    DOI: 10.1111/j.1467-985X.2005.00375.x
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    References listed on IDEAS

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    1. Sue Duval & Richard Tweedie, 2000. "Trim and Fill: A Simple Funnel-Plot–Based Method of Testing and Adjusting for Publication Bias in Meta-Analysis," Biometrics, The International Biometric Society, vol. 56(2), pages 455-463, June.
    2. J. L. Hutton & Paula R. Williamson, 2000. "Bias in meta‐analysis due to outcome variable selection within studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(3), pages 359-370.
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    Cited by:

    1. N. T. Longford, 2006. "Correspondence," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 647-648, July.
    2. Richard D. Riley, 2009. "Multivariate meta‐analysis: the effect of ignoring within‐study correlation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(4), pages 789-811, October.
    3. James Carpenter & Gerta Rücker & Guido Schwarzer, 2011. "Assessing the Sensitivity of Meta-analysis to Selection Bias: A Multiple Imputation Approach," Biometrics, The International Biometric Society, vol. 67(3), pages 1066-1072, September.

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