Three-level meta-analysis of dependent effect sizes

Although dependence in effect sizes is ubiquitous, commonly used meta-analytic methods assume independent effect sizes. We describe and illustrate three-level extensions of a mixed effects meta-analytic model that accounts for various sources of dependence within and across studies, because multilev...

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Published in:	Behavior research methods Vol. 45; no. 2; pp. 576 - 594
Main Authors:	Van den Noortgate, Wim, López-López, José Antonio, Marín-Martínez, Fulgencio, Sánchez-Meca, Julio
Format:	Journal Article
Language:	English
Published:	New York Springer-Verlag 01.06.2013 Springer Nature B.V
Subjects:	Behavioral Science and Psychology Bias Children & youth Cognitive Psychology Errors Imputing Internet Meta-analysis Meta-Analysis as Topic Models, Psychological Models, Statistical Models, Theoretical Multivariate Analysis Psychological tests Psychology Sampling Sampling Studies Simulation Studies Systematic review Multiple outcomes Multilevel Dependence Meta-analysis
ISSN:	1554-3528, 1554-351X, 1554-3528
Online Access:	Get full text
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Abstract	Although dependence in effect sizes is ubiquitous, commonly used meta-analytic methods assume independent effect sizes. We describe and illustrate three-level extensions of a mixed effects meta-analytic model that accounts for various sources of dependence within and across studies, because multilevel extensions of meta-analytic models still are not well known. We also present a three-level model for the common case where, within studies, multiple effect sizes are calculated using the same sample. Whereas this approach is relatively simple and does not require imputing values for the unknown sampling covariances, it has hardly been used, and its performance has not been empirically investigated. Therefore, we set up a simulation study, showing that also in this situation, a three-level approach yields valid results: Estimates of the treatment effects and the corresponding standard errors are unbiased.
AbstractList	Although dependence in effect sizes is ubiquitous, commonly used meta-analytic methods assume independent effect sizes. We describe and illustrate three-level extensions of a mixed effects meta-analytic model that accounts for various sources of dependence within and across studies, because multilevel extensions of meta-analytic models still are not well known. We also present a three-level model for the common case where, within studies, multiple effect sizes are calculated using the same sample. Whereas this approach is relatively simple and does not require imputing values for the unknown sampling covariances, it has hardly been used, and its performance has not been empirically investigated. Therefore, we set up a simulation study, showing that also in this situation, a three-level approach yields valid results: Estimates of the treatment effects and the corresponding standard errors are unbiased. Although dependence in effect sizes is ubiquitous, commonly used meta-analytic methods assume independent effect sizes. We describe and illustrate three-level extensions of a mixed effects meta-analytic model that accounts for various sources of dependence within and across studies, because multilevel extensions of meta-analytic models still are not well known. We also present a three-level model for the common case where, within studies, multiple effect sizes are calculated using the same sample. Whereas this approach is relatively simple and does not require imputing values for the unknown sampling covariances, it has hardly been used, and its performance has not been empirically investigated. Therefore, we set up a simulation study, showing that also in this situation, a three-level approach yields valid results: Estimates of the treatment effects and the corresponding standard errors are unbiased. [PUBLICATION ABSTRACT] Although dependence in effect sizes is ubiquitous, commonly used meta-analytic methods assume independent effect sizes. We describe and illustrate three-level extensions of a mixed effects meta-analytic model that accounts for various sources of dependence within and across studies, because multilevel extensions of meta-analytic models still are not well known. We also present a three-level model for the common case where, within studies, multiple effect sizes are calculated using the same sample. Whereas this approach is relatively simple and does not require imputing values for the unknown sampling covariances, it has hardly been used, and its performance has not been empirically investigated. Therefore, we set up a simulation study, showing that also in this situation, a three-level approach yields valid results: Estimates of the treatment effects and the corresponding standard errors are unbiased.Although dependence in effect sizes is ubiquitous, commonly used meta-analytic methods assume independent effect sizes. We describe and illustrate three-level extensions of a mixed effects meta-analytic model that accounts for various sources of dependence within and across studies, because multilevel extensions of meta-analytic models still are not well known. We also present a three-level model for the common case where, within studies, multiple effect sizes are calculated using the same sample. Whereas this approach is relatively simple and does not require imputing values for the unknown sampling covariances, it has hardly been used, and its performance has not been empirically investigated. Therefore, we set up a simulation study, showing that also in this situation, a three-level approach yields valid results: Estimates of the treatment effects and the corresponding standard errors are unbiased.
Author	López-López, José Antonio Van den Noortgate, Wim Marín-Martínez, Fulgencio Sánchez-Meca, Julio
Author_xml	– sequence: 1 givenname: Wim surname: Van den Noortgate fullname: Van den Noortgate, Wim email: wim.vandennoortgate@kuleuven-kortrijk.be organization: Faculty of Psychology and Educational Sciences, University of Leuven – sequence: 2 givenname: José Antonio surname: López-López fullname: López-López, José Antonio organization: Universidad de Murcia – sequence: 3 givenname: Fulgencio surname: Marín-Martínez fullname: Marín-Martínez, Fulgencio organization: Universidad de Murcia – sequence: 4 givenname: Julio surname: Sánchez-Meca fullname: Sánchez-Meca, Julio organization: Universidad de Murcia
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/23055166$$D View this record in MEDLINE/PubMed
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Snippet	Although dependence in effect sizes is ubiquitous, commonly used meta-analytic methods assume independent effect sizes. We describe and illustrate three-level...
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SubjectTerms	Behavioral Science and Psychology Bias Children & youth Cognitive Psychology Errors Imputing Internet Meta-analysis Meta-Analysis as Topic Models, Psychological Models, Statistical Models, Theoretical Multivariate Analysis Psychological tests Psychology Sampling Sampling Studies Simulation Studies Systematic review
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Title	Three-level meta-analysis of dependent effect sizes
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