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

The Optimising Analysis of Stroke Trials Collaboration, OAST

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


Authors

OAST The Optimising Analysis of Stroke Trials Collaboration



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

Citation

The Optimising Analysis of Stroke Trials Collaboration, O. (2008). Calculation of sample size for stroke trials assessing functional outcome: comparison of binary and ordinal approaches. International Journal of Stroke, 3(2), https://doi.org/10.1111/j.1747-4949.2008.00184.x

Journal Article Type Article
Publication Date May 1, 2008
Deposit Date Apr 25, 2008
Publicly Available Date May 1, 2008
Journal International Journal of Stroke
Print ISSN 1747-4930
Electronic ISSN 1747-4949
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 3
Issue 2
DOI https://doi.org/10.1111/j.1747-4949.2008.00184.x
Public URL https://nottingham-repository.worktribe.com/output/1015299
Publisher URL http://www.blackwellpublishing.com/
Additional Information The definitive version is available at www.blackwell-synergy.com

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