Correlated data analysis : modeling, analytics, and applications / Peter X.-K. Song.
Material type: TextLanguage: English Series: Springer series in statisticsPublication details: New York : Springer, c2007. Description: xv, 346 p. : ill. ; 24 cmISBN: 9780387713922 (acidfree paper); 0387713921 (acidfree paper); 9780387713939 (e-ISBN)Subject(s): Correlation (Statistics) | Generalized estimating equationsDDC classification: 519.537 LOC classification: QA278.2 | .S615 2007Online resources: WorldCat details | E-book FulltextItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|---|
E-Book | Dr. S. R. Lasker Library, EWU E-book | Non-fiction | 519.537 SOC 2007 (Browse shelf(Opens below)) | Not for loan | ||||
Text | Dr. S. R. Lasker Library, EWU Reserve Section | Non-fiction | 519.537 SOC 2007 (Browse shelf(Opens below)) | C-1 | Not For Loan | 26630 | ||
Text | Dr. S. R. Lasker Library, EWU Reserve Section | Non-fiction | 519.537 SOC 2007 (Browse shelf(Opens below)) | C-2 | Not For Loan | 26890 | ||
Text | Dr. S. R. Lasker Library, EWU Circulation Section | Non-fiction | 519.537 SOC 2007 (Browse shelf(Opens below)) | C-3 | Available | 26891 |
Includes bibliographical references and index.
TOC 1. Introduction and examples --
2. Dispersion models --
3. Inference functions --
4. Modeling correlated data --
5. Marginal generalized linear models --
6. Vector generalized linear models --
7. Mixed-effects models: likelihood-based inference --
8. Mixed-effects models: Bayesian inference --
9. Linear predictors --
10. Generalized state space models --
11. Generalized state space models for longitudinal binomial data --
12. Generalized state space models for longitudinal count data --
13. Missing data in longitudinal studie
Summary:
This book covers recent developments in correlated data analysis, using the class of dispersion models as marginal components in the formulation of joint models for correlated data. Much new material Read more...
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Saifun Momota
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