Correlated data analysis : modeling, analytics, and applications / Peter X.-K. Song.

By: Song, Peter X.-K (Xue-Kun), 1964-Material type: Text

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 Fulltext

Contents:

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: 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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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Barcode
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

Total holds: 0

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...

Saifun Momota

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