Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials
Background: Most large acute stroke trials have been neutral. Functional outcome is usually analysed using a yes or no answer, e.g. death or dependency vs. independence. We assessed which statistical approaches are most efficient in analysing outcomes from stroke trials. Methods: Individual patie...
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| Format: | Article |
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American Heart Association
2007
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| Online Access: | https://eprints.nottingham.ac.uk/947/ |
| _version_ | 1848790509271646208 |
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| author | Bath, Philip M.W. |
| author_facet | Bath, Philip M.W. |
| author_sort | Bath, Philip M.W. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Background: Most large acute stroke trials have been neutral. Functional outcome is usually analysed using a yes or no answer, e.g. death or dependency vs. independence. We assessed which statistical approaches are most efficient in analysing outcomes from stroke trials.
Methods: Individual patient data from acute, rehabilitation and stroke unit trials studying the effects of interventions which alter functional outcome were assessed. Outcomes included modified Rankin Scale, Barthel Index, and ‘3 questions’. Data were analysed using a variety of approaches which compare two treatment groups. The results for each statistical test for each trial were then compared.
Results: Data from 55 datasets were obtained (47 trials, 54,173 patients). The test results differed substantially so that approaches which use the ordered nature of functional outcome data (ordinal logistic regression, t-test, robust ranks test, bootstrapping the difference in mean rank) were more efficient statistically than those which collapse the data into 2 groups (chi square) (ANOVA p<0.001). The findings were consistent across different types and sizes of trial and for the different measures of functional outcome.
Conclusions: When analysing functional outcome from stroke trials, statistical tests which use the original ordered data are more efficient and more likely to yield reliable results. Suitable approaches included ordinal logistic regression, t-test, and robust ranks test. |
| first_indexed | 2025-11-14T18:13:45Z |
| format | Article |
| id | nottingham-947 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:13:45Z |
| publishDate | 2007 |
| publisher | American Heart Association |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-9472024-08-15T15:33:28Z https://eprints.nottingham.ac.uk/947/ Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials Bath, Philip M.W. Background: Most large acute stroke trials have been neutral. Functional outcome is usually analysed using a yes or no answer, e.g. death or dependency vs. independence. We assessed which statistical approaches are most efficient in analysing outcomes from stroke trials. Methods: Individual patient data from acute, rehabilitation and stroke unit trials studying the effects of interventions which alter functional outcome were assessed. Outcomes included modified Rankin Scale, Barthel Index, and ‘3 questions’. Data were analysed using a variety of approaches which compare two treatment groups. The results for each statistical test for each trial were then compared. Results: Data from 55 datasets were obtained (47 trials, 54,173 patients). The test results differed substantially so that approaches which use the ordered nature of functional outcome data (ordinal logistic regression, t-test, robust ranks test, bootstrapping the difference in mean rank) were more efficient statistically than those which collapse the data into 2 groups (chi square) (ANOVA p<0.001). The findings were consistent across different types and sizes of trial and for the different measures of functional outcome. Conclusions: When analysing functional outcome from stroke trials, statistical tests which use the original ordered data are more efficient and more likely to yield reliable results. Suitable approaches included ordinal logistic regression, t-test, and robust ranks test. American Heart Association 2007-06 Article PeerReviewed Bath, Philip M.W. (2007) Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials. Stroke, 38 (6). pp. 1911-1915. ISSN 1524-4628 stroke; randomised controlled trial; statistical analysis http://stroke.ahajournals.org/content/38/6/1911 doi:10.1161/STROKEAHA.106.474080 doi:10.1161/STROKEAHA.106.474080 |
| spellingShingle | stroke; randomised controlled trial; statistical analysis Bath, Philip M.W. Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials |
| title | Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials |
| title_full | Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials |
| title_fullStr | Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials |
| title_full_unstemmed | Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials |
| title_short | Can we improve the statistical analysis of stroke trials? Statistical re-analysis of functional outcomes in stroke trials |
| title_sort | can we improve the statistical analysis of stroke trials? statistical re-analysis of functional outcomes in stroke trials |
| topic | stroke; randomised controlled trial; statistical analysis |
| url | https://eprints.nottingham.ac.uk/947/ https://eprints.nottingham.ac.uk/947/ https://eprints.nottingham.ac.uk/947/ |