Missing variability in meta-analysis : is imputing always good?
This paper examines the implications of the present approaches in handling missing variability in meta analysis on the overall standard error (SE) of the estimate. The approaches are (1) exclusion of the studies with missing standard deviations (SDs) and (2) imputation of the missing SDs. The d...
| Main Authors: | , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2006
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/5555/ http://irep.iium.edu.my/5555/1/ICSTIE.uitm.pdf |
| _version_ | 1848776524288753664 |
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| author | Nik Idris, Nik Ruzni Abdullah, Mimi Hafizah |
| author_facet | Nik Idris, Nik Ruzni Abdullah, Mimi Hafizah |
| author_sort | Nik Idris, Nik Ruzni |
| building | IIUM Repository |
| collection | Online Access |
| description | This paper examines the implications of the present approaches in handling missing variability in meta analysis on the overall standard error (SE) of the estimate. The approaches are (1) exclusion of the studies with missing standard deviations (SDs) and (2) imputation of the missing SDs. The data was simulated with the SDs assumed to be missing according three scenarios, namely, missing completely at random (MCAR), missing at random (MAR) and not missing at random (NMAR). The study demonstrates that imputation is preferable over excluding the studies with missing standard deviations if the the missing variability occurs completely at random, or if the mechanism for missing variability depends on the size of the studies. However if studies with larger variability measures tend not to report the standard deviations, then imputation will lead to a bias in the standard error of the estimates. As the later case is impossible to ascertain, it is thus recommended that an analysis based upon studies with full available data and imputed data be carried out, and comparison between the two results are made. |
| first_indexed | 2025-11-14T14:31:27Z |
| format | Proceeding Paper |
| id | iium-5555 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T14:31:27Z |
| publishDate | 2006 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-55552012-08-16T07:21:16Z http://irep.iium.edu.my/5555/ Missing variability in meta-analysis : is imputing always good? Nik Idris, Nik Ruzni Abdullah, Mimi Hafizah HA Statistics This paper examines the implications of the present approaches in handling missing variability in meta analysis on the overall standard error (SE) of the estimate. The approaches are (1) exclusion of the studies with missing standard deviations (SDs) and (2) imputation of the missing SDs. The data was simulated with the SDs assumed to be missing according three scenarios, namely, missing completely at random (MCAR), missing at random (MAR) and not missing at random (NMAR). The study demonstrates that imputation is preferable over excluding the studies with missing standard deviations if the the missing variability occurs completely at random, or if the mechanism for missing variability depends on the size of the studies. However if studies with larger variability measures tend not to report the standard deviations, then imputation will lead to a bias in the standard error of the estimates. As the later case is impossible to ascertain, it is thus recommended that an analysis based upon studies with full available data and imputed data be carried out, and comparison between the two results are made. 2006-12-08 Proceeding Paper NonPeerReviewed application/pdf en http://irep.iium.edu.my/5555/1/ICSTIE.uitm.pdf Nik Idris, Nik Ruzni and Abdullah, Mimi Hafizah (2006) Missing variability in meta-analysis : is imputing always good? In: International Conference on Science & Technology: Application in Industry & Education (2006), 8-9 December, 2006, Penang, Malaysia. http://www3.uitm.edu.my/penanglbm/infoterkini/ind |
| spellingShingle | HA Statistics Nik Idris, Nik Ruzni Abdullah, Mimi Hafizah Missing variability in meta-analysis : is imputing always good? |
| title | Missing variability in meta-analysis : is imputing always good? |
| title_full | Missing variability in meta-analysis : is imputing always good? |
| title_fullStr | Missing variability in meta-analysis : is imputing always good? |
| title_full_unstemmed | Missing variability in meta-analysis : is imputing always good? |
| title_short | Missing variability in meta-analysis : is imputing always good? |
| title_sort | missing variability in meta-analysis : is imputing always good? |
| topic | HA Statistics |
| url | http://irep.iium.edu.my/5555/ http://irep.iium.edu.my/5555/ http://irep.iium.edu.my/5555/1/ICSTIE.uitm.pdf |