Intended for healthcare professionals

Research Methods & Reporting Statistics Notes

Comparisons within randomised groups can be very misleading

BMJ 2011; 342 doi: (Published 06 May 2011) Cite this as: BMJ 2011;342:d561
  1. J Martin Bland, professor of health statistics1,
  2. Douglas G Altman, professor of statistics in medicine2
  1. 1Department of Health Sciences, University of York, York YO10 5DD
  2. 2Centre for Statistics in Medicine, University of Oxford, Oxford OX2 6UD
  1. Correspondence to: Professor M Bland martin.bland{at}

When we randomise trial participants into two or more intervention groups, we do this to remove bias; the groups will, on average, be comparable in every respect except the treatment which they receive. Provided the trial is well conducted, without other sources of bias, any difference in the outcome of the groups can then reasonably be attributed to the different interventions received. In a previous note we discussed the analysis of those trials in which the primary outcome measure is also measured at baseline. We discussed several valid analyses, observing that “analysis of covariance” (a regression method) is the method of choice.1

Rather than comparing the randomised groups directly, however, researchers sometimes look at the change in the measurement between baseline and the end of the trial; they test whether there was a significant change from baseline, separately in each randomised group. They may then report that this difference is significant in one group but not in the other, and conclude that this is evidence that the groups, and hence the treatments, are different. One such example was a recent trial in …

View Full Text