The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations

Abstract— The choice between the fixed and random effects model for providing an overall meta analysis estimate in continuous data may affect the accuracy of these estimates. For studies with complete information, the Cochrane’s Q-test could provide some guide on the choice, although the power o...

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Main Authors:	Nik Ruzni, Nik Idris, Sarudin, Norraida
Format:	Conference or Workshop Item
Language:	English
Published:	2010
Subjects:	HA Statistics QA75 Electronic computers. Computer science
Online Access:	http://irep.iium.edu.my/5113/ http://irep.iium.edu.my/5113/ http://irep.iium.edu.my/5113/ http://irep.iium.edu.my/5113/1/ICKD2010.pdf

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recordtype	eprints
spelling	iium-51132012-01-09T12:20:03Z http://irep.iium.edu.my/5113/ The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations Nik Ruzni, Nik Idris Sarudin, Norraida HA Statistics QA75 Electronic computers. Computer science Abstract— The choice between the fixed and random effects model for providing an overall meta analysis estimate in continuous data may affect the accuracy of these estimates. For studies with complete information, the Cochrane’s Q-test could provide some guide on the choice, although the power of this test is quite low. If the study- level standard deviations (SDs) are not completely reported or “missing”, selection of meta analysis model should be done with more caution. Many studies suggest that imputation is a good way of recovering the lost information in the effect size estimate and the corresponding standard error. In this article, we compare empirically, the effects of imputation of the missing SDs on the overall meta analysis estimates based on both the fixed and random effect model. The results suggest imputation is recommended to estimate the overall effect size. However, to estimate its corresponding standard error (SE), imputation is recommended for the estimates based on the random effect model. If the fixed effect model is used, imputation may lead to bias estimates of the SE. 2010-03-19 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/5113/1/ICKD2010.pdf Nik Ruzni, Nik Idris and Sarudin, Norraida (2010) The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations. In: 2010 Second International Conference on Computer Engineering and Applications, 19-21 March, 2010, Bali Island, Indonesia. http://www.computer.org/portal/web/csdl/doi/10.1109/ICCEA.2010.265 DOI : 10.1109/ICCEA.2010.265
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	HA Statistics QA75 Electronic computers. Computer science
spellingShingle	HA Statistics QA75 Electronic computers. Computer science Nik Ruzni, Nik Idris Sarudin, Norraida The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations
description	Abstract— The choice between the fixed and random effects model for providing an overall meta analysis estimate in continuous data may affect the accuracy of these estimates. For studies with complete information, the Cochrane’s Q-test could provide some guide on the choice, although the power of this test is quite low. If the study- level standard deviations (SDs) are not completely reported or “missing”, selection of meta analysis model should be done with more caution. Many studies suggest that imputation is a good way of recovering the lost information in the effect size estimate and the corresponding standard error. In this article, we compare empirically, the effects of imputation of the missing SDs on the overall meta analysis estimates based on both the fixed and random effect model. The results suggest imputation is recommended to estimate the overall effect size. However, to estimate its corresponding standard error (SE), imputation is recommended for the estimates based on the random effect model. If the fixed effect model is used, imputation may lead to bias estimates of the SE.
format	Conference or Workshop Item
author	Nik Ruzni, Nik Idris Sarudin, Norraida
author_facet	Nik Ruzni, Nik Idris Sarudin, Norraida
author_sort	Nik Ruzni, Nik Idris
title	The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations
title_short	The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations
title_full	The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations
title_fullStr	The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations
title_full_unstemmed	The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations
title_sort	effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations
publishDate	2010
url	http://irep.iium.edu.my/5113/ http://irep.iium.edu.my/5113/ http://irep.iium.edu.my/5113/ http://irep.iium.edu.my/5113/1/ICKD2010.pdf
first_indexed	2023-09-18T20:13:36Z
last_indexed	2023-09-18T20:13:36Z
_version_	1777407640259788800

The effects of the choice of meta analysis model on the overall estimates for continuous data with missing standard deviations

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