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dc.contributor.authorKonstantopoulos, Spyrosen_US
dc.date.accessioned2011-09-13en_US
dc.date.accessioned2011-11-23T11:39:05Z-
dc.date.available2011-11-23T11:39:05Z-
dc.date.issued2011en_US
dc.identifier.piurn:nbn:de:101:1-201105173145en_US
dc.identifier.urihttp://hdl.handle.net/10419/51903-
dc.description.abstractMeta-analytic methods have been widely applied to education, medicine, and the social sciences. Much of meta-analytic data are hierarchically structured since effect size estimates are nested within studies, and in turn studies can be nested within level-3 units such as laboratories or investigators, and so forth. Thus, multilevel models are a natural framework for analyzing meta-analytic data. This paper discusses the application of a Fisher scoring method in two- and three-level meta-analysis that takes into account random variation at the second and at the third levels. The usefulness of the model is demonstrated using data that provide information about school calendar types. SAS proc mixed and HLM can be used to compute the estimates of fixed effects and variance components.en_US
dc.language.isoengen_US
dc.publisherIZA Bonnen_US
dc.relation.ispartofseriesDiscussion paper series // Forschungsinstitut zur Zukunft der Arbeit 5678en_US
dc.subject.jelC00en_US
dc.subject.ddc330en_US
dc.subject.keywordmultilevel modelsen_US
dc.subject.keywordmeta-analysisen_US
dc.subject.keywordrandom effectsen_US
dc.titleFixed effects and variance components estimation in three-level meta-analysisen_US
dc.typeWorking Paperen_US
dc.identifier.ppn668199628en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:IZA Discussion Papers, Forschungsinstitut zur Zukunft der Arbeit (IZA)

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