An empirical comparison of meta analysis models for continuous data with missing standard deviations

An empirical comparison of meta analysis models for continuous data with missing standard deviations

Abstract: 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...

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Main Authors: Nik Idris, Nik Ruzni, Saidin, Norraida
Format: Article
Language:English
Published: InterStat (Virginia Tech) 2011
Subjects:
HA Statistics
Online Access:http://irep.iium.edu.my/5544/
http://irep.iium.edu.my/5544/
http://irep.iium.edu.my/5544/1/1105002.pdf
id iium-5544
recordtype eprints
spelling iium-55442011-11-22T00:40:53Z http://irep.iium.edu.my/5544/ An empirical comparison of meta analysis models for continuous data with missing standard deviations Nik Idris, Nik Ruzni Saidin, Norraida HA Statistics Abstract: 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 InterStat (Virginia Tech) 2011-05 Article PeerReviewed application/pdf en http://irep.iium.edu.my/5544/1/1105002.pdf Nik Idris, Nik Ruzni and Saidin, Norraida (2011) An empirical comparison of meta analysis models for continuous data with missing standard deviations. InterStat. ISSN 1941-689X http://interstat.statjournals.net/YEAR/2011/abstracts/1105002.php
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
Saidin, Norraida
An empirical comparison of meta analysis models for continuous data with missing standard deviations
description Abstract: 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
Saidin, Norraida
author_facet Nik Idris, Nik Ruzni
Saidin, Norraida
author_sort Nik Idris, Nik Ruzni
title An empirical comparison of meta analysis models for continuous data with missing standard deviations
title_short An empirical comparison of meta analysis models for continuous data with missing standard deviations
title_full An empirical comparison of meta analysis models for continuous data with missing standard deviations
title_fullStr An empirical comparison of meta analysis models for continuous data with missing standard deviations
title_full_unstemmed An empirical comparison of meta analysis models for continuous data with missing standard deviations
title_sort empirical comparison of meta analysis models for continuous data with missing standard deviations
publisher InterStat (Virginia Tech)
publishDate 2011
url http://irep.iium.edu.my/5544/
http://irep.iium.edu.my/5544/
http://irep.iium.edu.my/5544/1/1105002.pdf
first_indexed 2018-09-07T03:17:07Z
last_indexed 2018-09-07T03:17:07Z
_version_ 1610917062207602688

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