Intended for healthcare professionals


Open access follow up for inflammatory bowel disease

BMJ 2000; 320 doi: (Published 24 June 2000) Cite this as: BMJ 2000;320:1730

Would have been better to use t test than Mann-Whitney U test

  1. Julie A Barber, research fellow,
  2. Simon G Thompson, director
  1. Medical Research Council Clinical Trials Unit, London NW1 2DA
  2. Medical Research Council Biostatistics Unit, Cambridge CB2 2SR
  3. Birmingham Women's Hospital, Birmingham B15 2TG
  4. Princess Royal Hospital, Telford TF1 6TF
  5. School of Postgraduate Studies in Medical and Health Care, Morriston Hospital, Swansea SA6 6NL
  6. Business School, University of Glamorgan, Pontypridd CF37 1DL
  7. Department of Health Sciences and Clinical Evaluation, University of York, York YO10 5DD

    EDITOR—Williams et al undertook a randomised trial to evaluate whether follow up of patients with inflammatory bowel disease is better with open access than with routine appointments.1 They compared primary and secondary care resource use and costs and concluded that open access follow up saves secondary care resources. This conclusion, however, is mistaken because they used inappropriate statistical methods.

    Resource use and cost data tend to have highly skewed distributions. As a result, the authors decided that standard parametric statistical methods were not appropriate and assessed significance by using a Mann-Whitney U test. Although this is consistent with conventional statistical guidelines,2 it does not address the question of interest in economic evaluations. As the authors themselves state, “economic analysis is mainly concerned with a comparison of means.” Use of a Mann-Whitney U test, however, makes an overall comparison of distributions in the two groups, in terms of both shape and location,3 and does not specifically test for a difference in means.

    The most appropriate simple method for comparing mean costs is the ordinary t test. By using the means and standard deviations in each group reported by the authors, we have calculated P values from t tests (table). The conclusions are dramatically different from the authors'. In …

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