Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/51903 
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dc.contributor.authorKonstantopoulos, Spyrosen
dc.date.accessioned2011-09-13-
dc.date.accessioned2011-11-23T11:39:05Z-
dc.date.available2011-11-23T11:39:05Z-
dc.date.issued2011-
dc.identifier.piurn:nbn:de:101:1-201105173145en
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
dc.language.isoengen
dc.publisher|aInstitute for the Study of Labor (IZA) |cBonnen
dc.relation.ispartofseries|aIZA Discussion Papers |x5678en
dc.subject.jelC00en
dc.subject.ddc330en
dc.subject.keywordmultilevel modelsen
dc.subject.keywordmeta-analysisen
dc.subject.keywordrandom effectsen
dc.titleFixed effects and variance components estimation in three-level meta-analysis-
dc.typeWorking Paperen
dc.identifier.ppn668199628en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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