Sample size calculations for ordered categorical data

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Abstract

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.

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