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Marginal models : for dependent, clustered, and longitudinal categorical data / Wicher Bergsma, Marcel Croon, Jacques A. Hagenaars.

By: Bergsma, Wicher P, 1966-Contributor(s): Croon, Marcel A | Hagenaars, Jacques AMaterial type: TextTextLanguage: English Series: Statistics for social and behavioral sciencesPublication details: New York : Springer, c2009. Description: xi, 268 p. : ill. ; 24 cmISBN: 9780387096094 (hbk.); 0387096094 (hbk.); 9781441918734; 1441918736Subject(s): Social sciences -- Mathematical models | Social sciences -- Statistical methods | Social sciences -- ResearchDDC classification: 300.15118 LOC classification: HA29 | .B423 2009Online resources: WorldCat details | E-book Fulltext
Contents:
TOC Loglinear Marginal Models.- Nonloglinear Marginal Models.- Marginal Analysis of Longitudinal Data.- Causal Analyses: Structural Equation Models and (Quasi-)Experimental Designs.- Marginal modeling with latent variables.- Conclusions, Extensions, and Applications
Summary: Marginal models are often the best way of answering research questions involving dependent observations. This comprehensive overview of the basic principles of marginal modeling offers a wide range of possible applications through many real world examples.
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Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
E-Book E-Book EWU Library
E-book
Non-fiction 300.15118 BEM 2009 (Browse shelf(Opens below)) Not For Loan
Text Text EWU Library
Reserve Section
Non-fiction 300.15118 BEM 2009 (Browse shelf(Opens below)) C-1 Not For Loan 26620
Text Text EWU Library
Circulation Section
Non-fiction 300.15118 BEM 2009 (Browse shelf(Opens below)) C-2 Available 26888
Text Text EWU Library
Circulation Section
Non-fiction 300.15118 BEM 2009 (Browse shelf(Opens below)) C-3 Available 26889
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Includes bibliographical references and index.

TOC Loglinear Marginal Models.- Nonloglinear Marginal Models.- Marginal Analysis of Longitudinal Data.- Causal Analyses: Structural Equation Models and (Quasi-)Experimental Designs.- Marginal modeling with latent variables.- Conclusions, Extensions, and Applications

Marginal models are often the best way of answering research questions involving dependent observations. This comprehensive overview of the basic principles of marginal modeling offers a wide range of possible applications through many real world examples.

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