Fixed-effect versus random-effect model in meta-analysis: How to decide?
Interpretation of meta-analysis requires an appropriate understanding of its statistical methods. Data synthesis methods are the basis of the meta-analytic process, and a thorough knowledge of the models used is essential. The two most widely used methods for data synthesis are the ‘fixed-effect met...
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Main Author: | |
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Format: | Article |
Language: | English |
Published: |
Wolters Kluwer Medknow Publications
2025-01-01
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Series: | Indian Journal of Anaesthesia |
Subjects: | |
Online Access: | https://journals.lww.com/10.4103/ija.ija_1203_24 |
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Summary: | Interpretation of meta-analysis requires an appropriate understanding of its statistical methods. Data synthesis methods are the basis of the meta-analytic process, and a thorough knowledge of the models used is essential. The two most widely used methods for data synthesis are the ‘fixed-effect method’ and the ‘random-effect method’. The latter is commonly used when a ‘significant heterogeneity’ exists. This narrative review explains fixed- and random-effect models, the two most commonly used data synthesis models. |
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ISSN: | 0019-5049 0976-2817 |