On selection of models for continuos meta analysis data with incomplete variability measures

The choice between the fixed and random effects models for providing an overall meta analysis estimates may affect the accuracy of those estimates. When the study-level standard deviations (SDs) are not completely reported or are “missing” selection of a meta analysis model should be done with more...

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Main Authors:	Nik Idris, Nik Ruzni, Sarudin, Norraida
Format:	Article
Language:	English
Published:	Pushpa Publishing House 2011
Subjects:	Q Science (General)
Online Access:	http://irep.iium.edu.my/7217/ http://irep.iium.edu.my/7217/ http://irep.iium.edu.my/7217/1/FJMS-_Final_Version.pdf

id	iium-7217
recordtype	eprints
spelling	iium-72172011-12-12T00:31:28Z http://irep.iium.edu.my/7217/ On selection of models for continuos meta analysis data with incomplete variability measures Nik Idris, Nik Ruzni Sarudin, Norraida Q Science (General) The choice between the fixed and random effects models for providing an overall meta analysis estimates may affect the accuracy of those estimates. When the study-level standard deviations (SDs) are not completely reported or are “missing” selection of a meta analysis model should be done with more caution. In this article, we examine through a simulation study, the effects of the choice of meta analysis model and the techniques of imputation of the missing SDs on the overall meta analysis estimates. The results suggest that imputation should be adopted to estimate the overall effect size, irrespective of the model used. However, the accuracy of the estimates of the corresponding standard error (SE) are influenced by the imputation techniques. For estimates based on the fixed effect model, mean imputation provides better estimates than multiple imputation, while those based on the random effects model are the more robust of the techniques imputation used. Pushpa Publishing House 2011-12 Article PeerReviewed application/pdf en http://irep.iium.edu.my/7217/1/FJMS-_Final_Version.pdf Nik Idris, Nik Ruzni and Sarudin, Norraida (2011) On selection of models for continuos meta analysis data with incomplete variability measures. Far East Journal of Mathematical Sciences (FJMS), 59 (2). pp. 173-187. ISSN 0972-0871 (In Press) http://www.pphmj.com/journals/fjms.htm
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	Q Science (General)
spellingShingle	Q Science (General) Nik Idris, Nik Ruzni Sarudin, Norraida On selection of models for continuos meta analysis data with incomplete variability measures
description	The choice between the fixed and random effects models for providing an overall meta analysis estimates may affect the accuracy of those estimates. When the study-level standard deviations (SDs) are not completely reported or are “missing” selection of a meta analysis model should be done with more caution. In this article, we examine through a simulation study, the effects of the choice of meta analysis model and the techniques of imputation of the missing SDs on the overall meta analysis estimates. The results suggest that imputation should be adopted to estimate the overall effect size, irrespective of the model used. However, the accuracy of the estimates of the corresponding standard error (SE) are influenced by the imputation techniques. For estimates based on the fixed effect model, mean imputation provides better estimates than multiple imputation, while those based on the random effects model are the more robust of the techniques imputation used.
format	Article
author	Nik Idris, Nik Ruzni Sarudin, Norraida
author_facet	Nik Idris, Nik Ruzni Sarudin, Norraida
author_sort	Nik Idris, Nik Ruzni
title	On selection of models for continuos meta analysis data with incomplete variability measures
title_short	On selection of models for continuos meta analysis data with incomplete variability measures
title_full	On selection of models for continuos meta analysis data with incomplete variability measures
title_fullStr	On selection of models for continuos meta analysis data with incomplete variability measures
title_full_unstemmed	On selection of models for continuos meta analysis data with incomplete variability measures
title_sort	on selection of models for continuos meta analysis data with incomplete variability measures
publisher	Pushpa Publishing House
publishDate	2011
url	http://irep.iium.edu.my/7217/ http://irep.iium.edu.my/7217/ http://irep.iium.edu.my/7217/1/FJMS-_Final_Version.pdf
first_indexed	2023-09-18T20:16:30Z
last_indexed	2023-09-18T20:16:30Z
_version_	1777407823026585600

On selection of models for continuos meta analysis data with incomplete variability measures

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