Missing variability in meta-analysis : is imputing always good?

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...

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Main Authors: Nik Idris, Nik Ruzni, Abdullah, Mimi Hafizah
Format: Conference or Workshop Item
Language:English
Published: 2006
Subjects:
HA Statistics
Online Access:http://irep.iium.edu.my/5555/
http://irep.iium.edu.my/5555/
http://irep.iium.edu.my/5555/1/ICSTIE.uitm.pdf
id iium-5555
recordtype eprints
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 Conference or Workshop Item 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
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic HA Statistics
spellingShingle HA Statistics
Nik Idris, Nik Ruzni
Abdullah, Mimi Hafizah
Missing variability in meta-analysis : is imputing always good?
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.
format Conference or Workshop Item
author Nik Idris, Nik Ruzni
Abdullah, Mimi Hafizah
author_facet Nik Idris, Nik Ruzni
Abdullah, Mimi Hafizah
author_sort Nik Idris, Nik Ruzni
title Missing variability in meta-analysis : is imputing always good?
title_short 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_sort missing variability in meta-analysis : is imputing always good?
publishDate 2006
url http://irep.iium.edu.my/5555/
http://irep.iium.edu.my/5555/
http://irep.iium.edu.my/5555/1/ICSTIE.uitm.pdf
first_indexed 2023-09-18T20:14:12Z
last_indexed 2023-09-18T20:14:12Z
_version_ 1777407678352457728

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