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Meta-analysis without study-specific variance information: Heterogeneity case

Meta-analysis without study-specific variance information: Heterogeneity case
Meta-analysis without study-specific variance information: Heterogeneity case
The random effects model in meta-analysis is a standard statistical tool often used to analyze the effect sizes of the quantity of interest if there is heterogeneity between studies. In the special case considered here, meta-analytic data contain only the sample means in two treatment arms and the sample sizes, but no sample standard deviation. The statistical comparison between two arms for this case is not possible within the existing meta-analytic inference framework. Therefore, the main objective of this paper is to estimate the overall mean difference and associated variances, the between-study variance and the within-study variance, as specified as the important elements in the random effects model. These estimators are obtained using maximum likelihood estimation. The standard errors of the estimators and a quantification of the degree of heterogeneity are also investigated. A measure of heterogeneity is suggested which adjusts the original suggested measure of Higgins’ I2 for within study sample size. The performance of the proposed estimators is evaluated using simulations. It can be concluded that all estimated means converged to their associated true parameter values, and its standard errors tended to be small if the number of the studies involved in the meta-analysis was large. The proposed estimators could be favorably applied in a meta-analysis on comparing two surgeries for asymptomatic congenital lung malformations in young children.
0962-2802
Sangnawakij, Patarawan
e821a2a7-a89f-4172-9006-8a6c2db9add6
Bohning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Niwitpong, Sa-aat
f5bf8776-4843-4e5d-9b71-6bc8f8d122db
Adams, Stephen
a8ab38ba-e9b5-440a-8de1-2f065b3b7c3d
Stanton, Michael
eb3258f5-245b-454a-9556-9ef3d0ebb87d
Holling, Heinz
88d46f56-77ca-4d0e-b035-a51aff735435
Sangnawakij, Patarawan
e821a2a7-a89f-4172-9006-8a6c2db9add6
Bohning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Niwitpong, Sa-aat
f5bf8776-4843-4e5d-9b71-6bc8f8d122db
Adams, Stephen
a8ab38ba-e9b5-440a-8de1-2f065b3b7c3d
Stanton, Michael
eb3258f5-245b-454a-9556-9ef3d0ebb87d
Holling, Heinz
88d46f56-77ca-4d0e-b035-a51aff735435

Sangnawakij, Patarawan, Bohning, Dankmar, Niwitpong, Sa-aat, Adams, Stephen, Stanton, Michael and Holling, Heinz (2017) Meta-analysis without study-specific variance information: Heterogeneity case. Statistical Methods in Medical Research. (doi:10.1177/0962280217718867).

Record type: Article

Abstract

The random effects model in meta-analysis is a standard statistical tool often used to analyze the effect sizes of the quantity of interest if there is heterogeneity between studies. In the special case considered here, meta-analytic data contain only the sample means in two treatment arms and the sample sizes, but no sample standard deviation. The statistical comparison between two arms for this case is not possible within the existing meta-analytic inference framework. Therefore, the main objective of this paper is to estimate the overall mean difference and associated variances, the between-study variance and the within-study variance, as specified as the important elements in the random effects model. These estimators are obtained using maximum likelihood estimation. The standard errors of the estimators and a quantification of the degree of heterogeneity are also investigated. A measure of heterogeneity is suggested which adjusts the original suggested measure of Higgins’ I2 for within study sample size. The performance of the proposed estimators is evaluated using simulations. It can be concluded that all estimated means converged to their associated true parameter values, and its standard errors tended to be small if the number of the studies involved in the meta-analysis was large. The proposed estimators could be favorably applied in a meta-analysis on comparing two surgeries for asymptomatic congenital lung malformations in young children.

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R4_MA_without_var_heterogeneity_case - Accepted Manuscript
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More information

Accepted/In Press date: 6 July 2017
e-pub ahead of print date: 6 July 2017

Identifiers

Local EPrints ID: 419350
URI: http://eprints.soton.ac.uk/id/eprint/419350
ISSN: 0962-2802
PURE UUID: 0bdd07fa-3bb0-4bce-ab1c-b1385793aa9d
ORCID for Dankmar Bohning: ORCID iD orcid.org/0000-0003-0638-7106

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Date deposited: 11 Apr 2018 16:30
Last modified: 17 Dec 2019 01:39

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