Examining Intermediate Omitted Levels in Hierarchical Designs via Latent Variable Modeling. Issue 1 (2nd January 2016) - Raykov, Tenko; Patelis, Thanos; Marcoulides, George A.; Lee, Chun-Lung
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.