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Bias in meta‐analysis due to outcome variable selection within studies

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  • J. L. Hutton
  • Paula R. Williamson

Abstract

Although bias in meta‐analysis arising from selective publication has been studied, within‐study selection has received little attention. Chronic diseases often have several possible outcome variables. Methods based on the size of the effect allow results from studies with different outcomes to be combined. However, the possibility of selective reporting of outcomes must be considered. The effect of selective reporting on estimates of the size of the effect and significance levels is presented, and sensitivity analyses are suggested. Substantial publication bias could arise from multiple testing of outcomes in a study, followed by selective reporting. Two meta‐analyses, on anthelminth therapy and a treatment for incontinence, are reassessed allowing for within‐study selection, as it is clear that more outcomes had been measured than were reported. The sensitivity analyses show that the robustness of the anthelminth results is dependent on what assumption one makes about the reporting strategy for the largest trial. The possible influence of correlation between within‐child measurements was such that the conclusions could easily be reversed. The effect of a mild assumption on within‐trial selection alone could alter general recommendations about the treatment for incontinence.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:jorssc:v:49:y:2000:i:3:p:359-370
    DOI: 10.1111/1467-9876.00197
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    Cited by:

    1. Alex Eble & Peter Boone & Diana Elbourne, 2017. "On Minimizing the Risk of Bias in Randomized Controlled Trials in Economics," The World Bank Economic Review, World Bank, vol. 31(3), pages 687-707.
    2. Jing Wang & Qiguo Zhang & Rongfu Zhou & Bing Chen & Jian Ouyang, 2012. "High-Dose Chemotherapy Followed by Autologous Stem Cell Transplantation as a First-Line Therapy for High-Risk Primary Breast Cancer: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-8, March.
    3. Jamie J Kirkham & Doug G Altman & Paula R Williamson, 2010. "Bias Due to Changes in Specified Outcomes during the Systematic Review Process," PLOS ONE, Public Library of Science, vol. 5(3), pages 1-5, March.
    4. Nikolaos Pandis & Padhraig S Fleming & Helen Worthington & Kerry Dwan & Georgia Salanti, 2015. "Discrepancies in Outcome Reporting Exist Between Protocols and Published Oral Health Cochrane Systematic Reviews," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-10, September.
    5. Salandra, Rossella & Criscuolo, Paola & Salter, Ammon, 2021. "Directing scientists away from potentially biased publications: the role of systematic reviews in health care," Research Policy, Elsevier, vol. 50(1).
    6. Peter M. Fayers & David J. Hand, 2002. "Causal variables, indicator variables and measurement scales: an example from quality of life," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(2), pages 233-253, June.
    7. Salandra, Rossella, 2018. "Knowledge dissemination in clinical trials: Exploring influences of institutional support and type of innovation on selective reporting," Research Policy, Elsevier, vol. 47(7), pages 1215-1228.
    8. Kerry Dwan & Douglas G Altman & Juan A Arnaiz & Jill Bloom & An-Wen Chan & Eugenia Cronin & Evelyne Decullier & Philippa J Easterbrook & Erik Von Elm & Carrol Gamble & Davina Ghersi & John P A Ioannid, 2008. "Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias," PLOS ONE, Public Library of Science, vol. 3(8), pages 1-31, August.
    9. Piia K. Peura & Janne A. Martikainen & Timo T. Purmonen & Juha H. O. Turunen, 2012. "Sponsorship-Related Outcome Selection Bias in Published Economic Studies of Triptans," Medical Decision Making, , vol. 32(2), pages 237-245, March.
    10. Megan L Head & Luke Holman & Rob Lanfear & Andrew T Kahn & Michael D Jennions, 2015. "The Extent and Consequences of P-Hacking in Science," PLOS Biology, Public Library of Science, vol. 13(3), pages 1-15, March.
    11. 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.
    12. Eble, Alex & Boone, Peter & Elbourne, Diana, 2013. "Risk and evidence of bias in randomized controlled trials in economics," LSE Research Online Documents on Economics 121784, London School of Economics and Political Science, LSE Library.
    13. Wynanda A van Enst & Rob J P M Scholten & Lotty Hooft, 2012. "Identification of Additional Trials in Prospective Trial Registers for Cochrane Systematic Reviews," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-5, August.
    14. D. J. Bartholomew, 2002. "Discussion on the paper by Fayers and Hand," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(2), pages 253-261, June.

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