Sample size calculations for ordered categorical data

Stat Med. 1993 Dec 30;12(24):2257-71. doi: 10.1002/sim.4780122404.


Many clinical trials yield data on an ordered categorical scale such as very good, good, moderate, poor. Under the assumption of proportional odds, such data can be analysed using techniques of logistic regression. In simple comparisons of two treatments this approach becomes equivalent to the Mann-Whitney test. In this paper sample size formulae consistent with an eventual logistic regression analysis are derived. The influence on efficiency of the number and breadth of categories will be examined. Effects of misclassification and of stratification are discussed, and examples of the calculations are given.

MeSH terms

  • Bias
  • Clinical Trials as Topic / statistics & numerical data*
  • Data Interpretation, Statistical*
  • Humans
  • Logistic Models
  • Probability
  • Prognosis
  • Sampling Studies*
  • Treatment Failure
  • Treatment Outcome*