The effects of imputing the missing standard deviations on the standard error of meta analysis estimates
A common problem in the meta analysis of continuous data is that some studies do not report sufficient information to calculate the standard deviation (SDs) of the treatment effect. One of the approaches in handling this problem is through imputation. This article examines the empirical implications...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis
2009
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| Online Access: | http://irep.iium.edu.my/5530/1/PUBLISHED_ARTICLE.pdf |
| _version_ | 1796875270413615104 |
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| author | Nik Idris, Nik Ruzni Robertson, Chris |
| author_facet | Nik Idris, Nik Ruzni Robertson, Chris |
| author_sort | Nik Idris, Nik Ruzni |
| collection | IIUM |
| description | A common problem in the meta analysis of continuous data is that some studies do not report sufficient information to calculate the standard deviation (SDs) of the treatment effect. One of the approaches in handling this problem is through imputation. This article examines the empirical implications of imputing the missing SDs on the standard error (SE) of the overall meta analysis estimate. The simulation results show that if the SDs are missing under Missing Completely at Random and Missing at Random mechanism, imputation is recommended. With non random missing, imputation can lead to overestimation of the SE of the estimate. |
| first_indexed | 2024-03-05T22:36:21Z |
| format | Article |
| id | oai:generic.eprints.org:5530 |
| institution | International Islamic University Malaysia |
| language | English |
| last_indexed | 2024-03-05T22:36:21Z |
| publishDate | 2009 |
| publisher | Taylor & Francis |
| record_format | dspace |
| spelling | oai:generic.eprints.org:55302011-11-22T00:46:50Z http://irep.iium.edu.my/5530/ The effects of imputing the missing standard deviations on the standard error of meta analysis estimates Nik Idris, Nik Ruzni Robertson, Chris HA Statistics Q Science (General) A common problem in the meta analysis of continuous data is that some studies do not report sufficient information to calculate the standard deviation (SDs) of the treatment effect. One of the approaches in handling this problem is through imputation. This article examines the empirical implications of imputing the missing SDs on the standard error (SE) of the overall meta analysis estimate. The simulation results show that if the SDs are missing under Missing Completely at Random and Missing at Random mechanism, imputation is recommended. With non random missing, imputation can lead to overestimation of the SE of the estimate. Taylor & Francis 2009-03-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/5530/1/PUBLISHED_ARTICLE.pdf Nik Idris, Nik Ruzni and Robertson, Chris (2009) The effects of imputing the missing standard deviations on the standard error of meta analysis estimates. Communications in Statistics - Simulation and Computation, 38 (3). pp. 513-526. ISSN 0361-0918 (P), 1532-4141 (O) http://www.tandfonline.com/doi/pdf/10.1080/03610910802556106 10.1080/03610910802556106 |
| spellingShingle | HA Statistics Q Science (General) Nik Idris, Nik Ruzni Robertson, Chris The effects of imputing the missing standard deviations on the standard error of meta analysis estimates |
| title | The effects of imputing the missing standard deviations on the standard error of meta analysis estimates |
| title_full | The effects of imputing the missing standard deviations on the standard error of meta analysis estimates |
| title_fullStr | The effects of imputing the missing standard deviations on the standard error of meta analysis estimates |
| title_full_unstemmed | The effects of imputing the missing standard deviations on the standard error of meta analysis estimates |
| title_short | The effects of imputing the missing standard deviations on the standard error of meta analysis estimates |
| title_sort | effects of imputing the missing standard deviations on the standard error of meta analysis estimates |
| topic | HA Statistics Q Science (General) |
| url | http://irep.iium.edu.my/5530/1/PUBLISHED_ARTICLE.pdf |
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