Examining Intermediate Omitted Levels in Hierarchical Designs via Latent Variable Modeling. Issue 1 (2nd January 2016)

• Record Type: Journal Article
• Authors: Raykov, Tenko; Patelis, Thanos; Marcoulides, George A.; Lee, Chun-Lung
• Is Part Of: Structural equation modeling. Volume 23:Issue 1(2016)
• Page Start: 111
• Page End: 115
• Publication Date: 2016-01-02
• Subjects: hierarchical data -- interval estimation -- multilevel modeling -- proportion explained variance; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2014.938186
• Languages: English
• ISSNs: 1070-5511

Abstract

Abstract : This article outlines an interval estimation procedure that can be used in a 3-level setting to evaluate the proportion of outcome variance attributable to the second level of clustering. The method is useful for examining the necessity of including a possibly omitted intermediate level of nesting in analyses of data from a multilevel study, and represents an informative addendum to current statistical tests of second-level variance. The approach is developed within the framework of latent variable modeling and can be used as an aid in the process of choosing between 2-level and 3-level models in a hierarchical design. The discussed procedure is illustrated with an empirical example.