On pooling different levels of data in estimating parameters of continuous meta-analysis

A meta-analysis may be performed using aggregate data (AD) or an individual patient data (IPD). In practice, studies may be available at both IPD and AD level. In this situation, both the IPD and AD should be utilised in order to maximize the available information. Statistical advantages of combin...

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Main Authors:	Nik Idris, Nik Ruzni, Baharom, Suhaila
Format:	Article
Language:	English
Published:	World Academy of Science, Engineering and Technology 2014
Subjects:	Q Science (General)
Online Access:	http://irep.iium.edu.my/38056/ http://irep.iium.edu.my/38056/ http://irep.iium.edu.my/38056/1/Published_Paper.pdf

id	iium-38056
recordtype	eprints
spelling	iium-380562018-06-19T02:41:29Z http://irep.iium.edu.my/38056/ On pooling different levels of data in estimating parameters of continuous meta-analysis Nik Idris, Nik Ruzni Baharom, Suhaila Q Science (General) A meta-analysis may be performed using aggregate data (AD) or an individual patient data (IPD). In practice, studies may be available at both IPD and AD level. In this situation, both the IPD and AD should be utilised in order to maximize the available information. Statistical advantages of combining the studies from different level has not been fully explored. This study aims to quantify the statistical benefits of including available IPD when conducting a conventional summary-level meta-analysis. Simulated meta-analysis were used to assess the influence of the levels of data on overall meta-analysis estimates based on IPD-only, AD-only and the combination of IPD and AD (mixed data, MD), under different study scenario. The percentage relative bias (PRB), root mean-square-error (RMSE) and coverage probability were used to assess the efficiency of the overall estimates. The results demonstrate that available IPD should always be included in a conventional meta-analysis using summary level data as they would significantly increased the accuracy of the estimates. On the other hand, if more than 80% of the available data are at IPD level, including the AD does not provide significant differences in terms of accuracy of the estimates. Additionally, combining the IPD and AD has a moderating effects on the biasness of the estimates of the treatment effects as the IPD tends to overestimate the treatment effects, while the AD has the tendency to produce underestimated effect estimates. These results may provide some guide in deciding if significant benefit is gained by pooling the two levels of data when conducting meta-analysis. World Academy of Science, Engineering and Technology 2014-08-18 Article PeerReviewed application/pdf en http://irep.iium.edu.my/38056/1/Published_Paper.pdf Nik Idris, Nik Ruzni and Baharom, Suhaila (2014) On pooling different levels of data in estimating parameters of continuous meta-analysis. International Journal of Computer, Information, Systems and Control Engineering , 8 (8). pp. 1136-1139. ISSN 1307-6892 http://www.waset.org
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 Baharom, Suhaila On pooling different levels of data in estimating parameters of continuous meta-analysis
description	A meta-analysis may be performed using aggregate data (AD) or an individual patient data (IPD). In practice, studies may be available at both IPD and AD level. In this situation, both the IPD and AD should be utilised in order to maximize the available information. Statistical advantages of combining the studies from different level has not been fully explored. This study aims to quantify the statistical benefits of including available IPD when conducting a conventional summary-level meta-analysis. Simulated meta-analysis were used to assess the influence of the levels of data on overall meta-analysis estimates based on IPD-only, AD-only and the combination of IPD and AD (mixed data, MD), under different study scenario. The percentage relative bias (PRB), root mean-square-error (RMSE) and coverage probability were used to assess the efficiency of the overall estimates. The results demonstrate that available IPD should always be included in a conventional meta-analysis using summary level data as they would significantly increased the accuracy of the estimates. On the other hand, if more than 80% of the available data are at IPD level, including the AD does not provide significant differences in terms of accuracy of the estimates. Additionally, combining the IPD and AD has a moderating effects on the biasness of the estimates of the treatment effects as the IPD tends to overestimate the treatment effects, while the AD has the tendency to produce underestimated effect estimates. These results may provide some guide in deciding if significant benefit is gained by pooling the two levels of data when conducting meta-analysis.
format	Article
author	Nik Idris, Nik Ruzni Baharom, Suhaila
author_facet	Nik Idris, Nik Ruzni Baharom, Suhaila
author_sort	Nik Idris, Nik Ruzni
title	On pooling different levels of data in estimating parameters of continuous meta-analysis
title_short	On pooling different levels of data in estimating parameters of continuous meta-analysis
title_full	On pooling different levels of data in estimating parameters of continuous meta-analysis
title_fullStr	On pooling different levels of data in estimating parameters of continuous meta-analysis
title_full_unstemmed	On pooling different levels of data in estimating parameters of continuous meta-analysis
title_sort	on pooling different levels of data in estimating parameters of continuous meta-analysis
publisher	World Academy of Science, Engineering and Technology
publishDate	2014
url	http://irep.iium.edu.my/38056/ http://irep.iium.edu.my/38056/ http://irep.iium.edu.my/38056/1/Published_Paper.pdf
first_indexed	2023-09-18T20:54:37Z
last_indexed	2023-09-18T20:54:37Z
_version_	1777410220658524160

On pooling different levels of data in estimating parameters of continuous meta-analysis

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