Calculation of sample size for stroke trials assessing functional outcome: comparison of binary and ordinal approaches

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The Optimising Analysis of Stroke Trials Collaboration, OAST (2008) Calculation of sample size for stroke trials assessing functional outcome: comparison of binary and ordinal approaches. International Journal of Stroke, 3 (2). pp. 78-84. ISSN 1747-4949

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Abstract

Background Many acute stroke trials have given neutral

results. Sub-optimal statistical analyses may be failing to

detect efficacy. Methods which take account of the ordinal

nature of functional outcome data are more efficient. We

compare sample size calculations for dichotomous and ordinal

outcomes for use in stroke trials.

Methods Data from stroke trials studying the effects of

interventions known to positively or negatively alter functional

outcome – Rankin Scale and Barthel Index – were

assessed. Sample size was calculated using comparisons of

proportions, means, medians (according to Payne), and ordinal

data (according to Whitehead). The sample sizes gained

from each method were compared using Friedman 2 way

ANOVA.

Results Fifty-five comparisons (54 173 patients) of active vs.

control treatment were assessed. Estimated sample sizes

differed significantly depending on the method of calculation

(Po00001). The ordering of the methods showed that the

ordinal method of Whitehead and comparison of means

produced significantly lower sample sizes than the other

methods. The ordinal data method on average reduced sample

size by 28% (inter-quartile range 14–53%) compared with

the comparison of proportions; however, a 22% increase in

sample size was seen with the ordinal method for trials

assessing thrombolysis. The comparison of medians method

of Payne gave the largest sample sizes.

Conclusions Choosing an ordinal rather than binary method

of analysis allows most trials to be, on average, smaller by

approximately 28% for a given statistical power. Smaller trial

sample sizes may help by reducing time to completion, complexity,

and financial expense. However, ordinal methods

may not be optimal for interventions which both improve

functional outcome

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/1015299
Additional Information: The definitive version is available at www.blackwell-synergy.com
Schools/Departments: University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Medicine > Division of Clinical Neuroscience
Depositing User: Sayers, Hazel
Date Deposited: 25 Apr 2008 13:41
Last Modified: 04 May 2020 20:27
URI: https://eprints.nottingham.ac.uk/id/eprint/889

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