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ERIC Number: EJ782487
Record Type: Journal
Publication Date: 2003
Pages: 33
Abstractor: Author
Reference Count: 47
ISSN: ISSN-1076-9986
Estimating Multilevel Linear Models as Structural Equation Models
Bauer, Daniel J.
Journal of Educational and Behavioral Statistics, v28 n2 p135-167 2003
Multilevel linear models (MLMs) provide a powerful framework for analyzing data collected at nested or non-nested levels, such as students within classrooms. The current article draws on recent analytical and software advances to demonstrate that a broad class of MLMs may be estimated as structural equation models (SEMs). Moreover, within the SEM approach it is possible to include measurement models for predictors or outcomes, and to estimate the mediational pathways among predictors explicitly, tasks which are currently difficult with the conventional approach to multilevel modeling. The equivalency of the SEM approach with conventional methods for estimating MLMs is illustrated using empirical examples, including an example involving both multiple indicator latent factors for the outcomes and a causal chain for the predictors. The limitations of this approach for estimating MLMs are discussed and alternative approaches are considered. (Contains 2 tables, 8 figures and 10 notes.)
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: High Schools
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A