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Improving the accuracy of likelihood-based inference in meta-analysis and meta-regression
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Kosmidis, Ioannis, Guolo, A. and Varin, Cristiano (2017) Improving the accuracy of likelihood-based inference in meta-analysis and meta-regression. Biometrika, 104 (2). pp. 489-496. doi:10.1093/biomet/asx001
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Official URL: http://dx.doi.org/10.1093/biomet/asx001
Abstract
Random-effects models are frequently used to synthesize information from different studies in meta-analysis. While likelihood-based inference is attractive both in terms of limiting properties and of implementation, its application in random-effects meta-analysis may result in misleading conclusions, especially when the number of studies is small to moderate. The current paper shows how methodology that reduces the asymptotic bias of the maximum likelihood estimator of the variance component can also substantially improve inference about the mean effect size. The results are derived for the more general framework of random-effects meta-regression, which allows the mean effect size to vary with study-specific covariates.
| Item Type: | Journal Article | ||||||||
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| Subjects: | H Social Sciences > HA Statistics Q Science > QA Mathematics |
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| Divisions: | Faculty of Science > Statistics | ||||||||
| Library of Congress Subject Headings (LCSH): | Multilevel models (Statistics), Mathematical statistics, Meta-analysis, Regression analysis, Asymptotic distribution (Probability theory) | ||||||||
| Journal or Publication Title: | Biometrika | ||||||||
| Publisher: | Biometrika Trust | ||||||||
| ISSN: | 0006-3444 | ||||||||
| Official Date: | 1 September 2017 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 15 February 2018 | ||||||||
| Volume: | 104 | ||||||||
| Number: | 2 | ||||||||
| Page Range: | pp. 489-496 | ||||||||
| DOI: | 10.1093/biomet/asx001 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access |
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