ERIC Number: EJ1004545
Record Type: Journal
Publication Date: 2013-Apr
Pages: 18
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1076-9986
EISSN: N/A
Comparing Regression Coefficients between Nested Linear Models for Clustered Data with Generalized Estimating Equations
Yan, Jun; Aseltine, Robert H., Jr.; Harel, Ofer
Journal of Educational and Behavioral Statistics, v38 n2 p172-189 Apr 2013
Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The statistical problem is whether the coefficients associated with a given set of covariates change significantly when other covariates are added into the model as controls. Methods for such comparison exist for independent data but do not apply when data are clustered such as longitudinal or familial data. Under the framework of generalized estimating equations, the authors develop statistical methods for such comparison. The properties of the proposed estimator of the difference in regression coefficients between two models are studied asymptotically and for finite samples through simulation. Application of the method to data on changes in depression mood from adolescence through young adulthood reveals that the effect of age after controlling for work status and marital status, although still significant, is largely reduced. (Contains 5 tables and 1 figure.)
Descriptors: Computation, Regression (Statistics), Comparative Analysis, Models, Statistical Analysis, Generalization, Equations (Mathematics), Statistical Inference, Depression (Psychology), Adolescents, Young Adults, High School Students, Age Differences, Longitudinal Studies
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Publication Type: Journal Articles; Reports - Research
Education Level: High Schools; Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Massachusetts
Identifiers - Assessments and Surveys: Center for Epidemiologic Studies Depression Scale
Grant or Contract Numbers: N/A