Marginal models : for dependent, clustered, and longitudinal categorical data / Wicher Bergsma, Marcel Croon, Jacques A. Hagenaars.
By: Bergsma, Wicher P
Contributor(s): Croon, Marcel A
| Hagenaars, Jacques A
Material type: 



Item type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds |
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EWU Library E-book | Non-fiction | 300.15118 BEM 2009 (Browse shelf) | Not For Loan | ||||
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EWU Library Reserve Section | Non-fiction | 300.15118 BEM 2009 (Browse shelf) | C-1 | Not For Loan | 26620 | ||
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EWU Library Circulation Section | Non-fiction | 300.15118 BEM 2009 (Browse shelf) | C-2 | Available | 26888 | ||
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EWU Library Circulation Section | Non-fiction | 300.15118 BEM 2009 (Browse shelf) | C-3 | Available | 26889 |
Includes bibliographical references and index.
Table of contents 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.
Applied Statistics
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