Imputing missing standard deviations in meta-analyses can provide accurate results.
BACKGROUND AND OBJECTIVES: Many reports of randomized controlled trials (RCTs) fail to provide standard deviations (SDs) of their continuous outcome measures. Some meta-analysts substitute them by those reported in other studies, either from another meta-analysis or from other studies in the same m...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2006
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| _version_ | 1826302208871759872 |
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| author | Furukawa, T Barbui, C Cipriani, A Brambilla, P Watanabe, N |
| author_facet | Furukawa, T Barbui, C Cipriani, A Brambilla, P Watanabe, N |
| author_sort | Furukawa, T |
| collection | OXFORD |
| description | BACKGROUND AND OBJECTIVES: Many reports of randomized controlled trials (RCTs) fail to provide standard deviations (SDs) of their continuous outcome measures. Some meta-analysts substitute them by those reported in other studies, either from another meta-analysis or from other studies in the same meta-analysis. But the validity of such practices has never been empirically examined. METHODS: We compared the actual standardized mean difference (SMD) of individual RCTs and the meta-analytically pooled SMD of all RCTs against those based on the above-mentioned two imputation methods in two meta-analyses of antidepressants. RESULTS: Two meta-analyses included 39 RCTs of fluoxetine (n = 3,681) and 25 RCTs of amitriptyline (n = 1,832), which had actually reported means and SDs of the Hamilton Rating Scale for Depression. According to either of the two proposed imputation methods, the agreement between actual SMDs and imputed SMDs for individual RCTs was very good with ANOVA intraclass correlation coefficients between 0.61 and 0.97. The agreement between the actual pooled SMD and the imputed one was even better, with minimal differences in both their point estimates and 95% confidence intervals. CONCLUSION: For a systematic review where some of the identified trials do not report SDs, it appears safe to borrow SDs from other studies. |
| first_indexed | 2024-03-07T05:44:04Z |
| format | Journal article |
| id | oxford-uuid:e6987094-7179-4d22-b902-24ff5647e85f |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:44:04Z |
| publishDate | 2006 |
| record_format | dspace |
| spelling | oxford-uuid:e6987094-7179-4d22-b902-24ff5647e85f2022-03-27T10:32:12ZImputing missing standard deviations in meta-analyses can provide accurate results.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e6987094-7179-4d22-b902-24ff5647e85fEnglishSymplectic Elements at Oxford2006Furukawa, TBarbui, CCipriani, ABrambilla, PWatanabe, N BACKGROUND AND OBJECTIVES: Many reports of randomized controlled trials (RCTs) fail to provide standard deviations (SDs) of their continuous outcome measures. Some meta-analysts substitute them by those reported in other studies, either from another meta-analysis or from other studies in the same meta-analysis. But the validity of such practices has never been empirically examined. METHODS: We compared the actual standardized mean difference (SMD) of individual RCTs and the meta-analytically pooled SMD of all RCTs against those based on the above-mentioned two imputation methods in two meta-analyses of antidepressants. RESULTS: Two meta-analyses included 39 RCTs of fluoxetine (n = 3,681) and 25 RCTs of amitriptyline (n = 1,832), which had actually reported means and SDs of the Hamilton Rating Scale for Depression. According to either of the two proposed imputation methods, the agreement between actual SMDs and imputed SMDs for individual RCTs was very good with ANOVA intraclass correlation coefficients between 0.61 and 0.97. The agreement between the actual pooled SMD and the imputed one was even better, with minimal differences in both their point estimates and 95% confidence intervals. CONCLUSION: For a systematic review where some of the identified trials do not report SDs, it appears safe to borrow SDs from other studies. |
| spellingShingle | Furukawa, T Barbui, C Cipriani, A Brambilla, P Watanabe, N Imputing missing standard deviations in meta-analyses can provide accurate results. |
| title | Imputing missing standard deviations in meta-analyses can provide accurate results. |
| title_full | Imputing missing standard deviations in meta-analyses can provide accurate results. |
| title_fullStr | Imputing missing standard deviations in meta-analyses can provide accurate results. |
| title_full_unstemmed | Imputing missing standard deviations in meta-analyses can provide accurate results. |
| title_short | Imputing missing standard deviations in meta-analyses can provide accurate results. |
| title_sort | imputing missing standard deviations in meta analyses can provide accurate results |
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