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Linear mixed models for longitudinal data

Record Type:	Electronic resources : Monograph/item
Title/Author:	Linear mixed models for longitudinal data/ Geert Verbeke, Geert Molenberghs.
Author:	Verbeke, Geert.
other author:	Molenberghs, Geert.
Published:	New York :Springer, : c2000.,
Description:	xxii, 568 p. :ill. ;25 cm.
Series:	Springer series in statistics
[NT 15003449]:	1. Introduction -- 2. Examples -- 3. A Model for Longitudinal Data -- 4. Exploratory Data Analysis -- 5. Estimation of the Marginal Model -- 6. Inference for the Marginal Model -- 7. Inference for the Random Effects -- 8. Fitting Linear Mixed Models with SAS -- 9. General Guidelines for Model Building -- 10. Exploring Serial Correlation -- 11. Local Influence for the Linear Mixed Model -- 12. The Heterogeneity Model -- 13. Conditional Linear Mixed Models -- 14. Exploring Incomplete Data -- 15. Joint Modeling of Measurements and Missingness -- 16. Simple Missing Data Methods -- 17. Selection Models -- 18. Pattern-Mixture Models -- 19. Sensitivity Analysis for Selection Models -- 20. Sensitivity Analysis for Pattern-Mixture Models -- 21. How Ignorable Is Missing At Random? -- 22. The Expectation-Maximization Algorithm -- 23. Design Considerations -- 24. Case Studies -- App. B. Technical Details for Sensitivity Analysis.
Subject:	Linear models (Statistics) -
Online resource:	https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=104522An electronic book accessible through the World Wide Web; click for information
ISBN:	038722775X (electronic bk.)

Linear mixed models for longitudinal data
Verbeke, Geert.

Linear mixed models for longitudinal data[electronic resource] /Geert Verbeke, Geert Molenberghs. - New York :Springer,c2000. - xxii, 568 p. :ill. ;25 cm. - Springer series in statistics.

Includes bibliographical references (p. [523]-553) and index.

1. Introduction -- 2. Examples -- 3. A Model for Longitudinal Data -- 4. Exploratory Data Analysis -- 5. Estimation of the Marginal Model -- 6. Inference for the Marginal Model -- 7. Inference for the Random Effects -- 8. Fitting Linear Mixed Models with SAS -- 9. General Guidelines for Model Building -- 10. Exploring Serial Correlation -- 11. Local Influence for the Linear Mixed Model -- 12. The Heterogeneity Model -- 13. Conditional Linear Mixed Models -- 14. Exploring Incomplete Data -- 15. Joint Modeling of Measurements and Missingness -- 16. Simple Missing Data Methods -- 17. Selection Models -- 18. Pattern-Mixture Models -- 19. Sensitivity Analysis for Selection Models -- 20. Sensitivity Analysis for Pattern-Mixture Models -- 21. How Ignorable Is Missing At Random? -- 22. The Expectation-Maximization Algorithm -- 23. Design Considerations -- 24. Case Studies -- App. B. Technical Details for Sensitivity Analysis.

Electronic reproduction.
Boulder, Colo. :
NetLibrary,
2004.

Available via World Wide Web.

ISBN: 038722775X (electronic bk.)Subjects--Topical Terms:

533190
Linear models (Statistics)
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QA279 / .V458 2000eb

Dewey Class. No.: 519.5/3

Linear mixed models for longitudinal data
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020 $a 038722775X (electronic bk.)
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035 $a 731017
040 $a N $c N $d OCLCQ $d OCL
049 $a AMFA
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100 $a Verbeke, Geert. $3 724603
245 1 0 $a Linear mixed models for longitudinal data $h [electronic resource] / $c Geert Verbeke, Geert Molenberghs.
260 $a New York : $c c2000. $b Springer,
300 $a xxii, 568 p. : $b ill. ; $c 25 cm.
440 0 $a Springer series in statistics
504 $a Includes bibliographical references (p. [523]-553) and index.
505 0 $a 1. Introduction -- 2. Examples -- 3. A Model for Longitudinal Data -- 4. Exploratory Data Analysis -- 5. Estimation of the Marginal Model -- 6. Inference for the Marginal Model -- 7. Inference for the Random Effects -- 8. Fitting Linear Mixed Models with SAS -- 9. General Guidelines for Model Building -- 10. Exploring Serial Correlation -- 11. Local Influence for the Linear Mixed Model -- 12. The Heterogeneity Model -- 13. Conditional Linear Mixed Models -- 14. Exploring Incomplete Data -- 15. Joint Modeling of Measurements and Missingness -- 16. Simple Missing Data Methods -- 17. Selection Models -- 18. Pattern-Mixture Models -- 19. Sensitivity Analysis for Selection Models -- 20. Sensitivity Analysis for Pattern-Mixture Models -- 21. How Ignorable Is Missing At Random? -- 22. The Expectation-Maximization Algorithm -- 23. Design Considerations -- 24. Case Studies -- App. B. Technical Details for Sensitivity Analysis.
533 $a Electronic reproduction. $b Boulder, Colo. : $c NetLibrary, $d 2004. $n Available via World Wide Web. $n Access may be limited to NetLibrary affiliated libraries.
650 $a Linear models (Statistics) $3 533190
650 $a Longitudinal method. $3 536787
650 $a Linear Models. $3 820716
650 $a Longitudinal Studies. $3 646448
650 $a Statistics $x methods. $3 773976
650 $a Mod墈les lin歋aires (Statistique) $3 817986
650 $a M歋thode longitudinale. $3 820717
655 $a Electronic books. $2 lcsh $3 542853
700 $a Molenberghs, Geert. $3 724602
710 $a NetLibrary, Inc. $3 542851
856 4 $3 Bibliographic record display $u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=104522 $z An electronic book accessible through the World Wide Web; click for information
994 $a 92 $b AMF