Statistics
Volume 178 - Issue 7

In reply: Covariate adjustment for prognostic baseline characteristics may decrease the sample size

Authors:  Anthony C Keech and Val J Gebski

Med J Aust 2003; 178 (7): 357-358. || doi: 10.5694/j.1326-5377.2003.tb05239.x
Published online: 7 April 2003
Download PDF (400 KB)
Share: Share on Blue Sky Share on Facebook Share on LinkedIn Share by email

In reply: While we agree that covariate adjustment during analysis can be a potential mechanism for reducing sample size (even when there is no imbalance in the important covariate levels between the treatment groups), unless such analyses are prospectively planned then they will not allow valid statistical inference. This is because post-hoc adjustment is an exploratory procedure and may have involved examining any number of potential covariates.

Further, to quantify any anticipated sample-size gains would depend on specifying likely maximum covariate imbalances, overall covariate distributions and plausible effects of treatment within the covariate levels during study design. In practice, the study would then have to meet these assumptions for the calculated sample-size gain to be achieved.

Covariate adjustment is an accepted practice for subsidiary analysis in clinical trials, and can take account of differential effects in imbalanced subgroups. For example, see the case of an apparent chance imbalance in numbers of women in the treatment arms of the HERO-2 trial, where investigators presented both unadjusted and adjusted results.1

Where important predictors of the clinical outcomes are expected to be variable for the population under study, a particularly useful approach is to stratify the randomisation by those predictors.2 Such stratification allows for valid adjusted analyses.3

Authors

  • Anthony C Keech
  • Val J Gebski

References

View this article on Wiley Online Library