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Beschreibung
This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place.
Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.
Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.
This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place.
Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.
Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.
Zusammenfassung
The SAS routines on mixed models have applications in many areas of
statistics, especially biostatistics, but the procedures are not well-
documented. Based on short courses given by the authors, this book
provides practical guidance for SAS users.
statistics, especially biostatistics, but the procedures are not well-
documented. Based on short courses given by the authors, this book
provides practical guidance for SAS users.
Inhaltsverzeichnis
Examples.- A Model for Longitudinal Data.- Exploratory Data Analysis.- Estimation of the Marginal Model.- Inference for the Marginal Model.- Inference for the Random Effects.- Fitting Linear Mixed Models with SAS.- General Guidelines for Model Building.- Exploring Serial Correlation.- Local Influence for the Linear Mixed Model.- The Heterogeneity Model.- Conditional Linear Mixed Models.- Exploring Incomplete Data.- Joint Modeling of Measurements and Missingness.- Simple Missing Data Methods.- Selection Models.- Pattern-Mixture Models.- Sensitivity Analysis for Selection Models.- Sensitivity Analysis for Pattern-Mixture Models.- How Ignorable Is Missing At Random ?.- The Expectation-Maximization Algorithm.- Design Considerations.- Case Studies.
Details
Erscheinungsjahr: | 2000 |
---|---|
Fachbereich: | Wahrscheinlichkeitstheorie |
Genre: | Importe, Mathematik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Reihe: | Springer Series in Statistics |
Inhalt: |
xxii
568 S. |
ISBN-13: | 9780387950273 |
ISBN-10: | 0387950273 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: |
Molenberghs, Geert
Verbeke, Geert |
Auflage: | 1st ed. 1997. 2nd printing 2000 |
Hersteller: |
Springer New York
Springer US, New York, N.Y. Springer Series in Statistics |
Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
Maße: | 235 x 155 x 32 mm |
Von/Mit: | Geert Molenberghs (u. a.) |
Erscheinungsdatum: | 16.06.2000 |
Gewicht: | 0,89 kg |
Zusammenfassung
The SAS routines on mixed models have applications in many areas of
statistics, especially biostatistics, but the procedures are not well-
documented. Based on short courses given by the authors, this book
provides practical guidance for SAS users.
statistics, especially biostatistics, but the procedures are not well-
documented. Based on short courses given by the authors, this book
provides practical guidance for SAS users.
Inhaltsverzeichnis
Examples.- A Model for Longitudinal Data.- Exploratory Data Analysis.- Estimation of the Marginal Model.- Inference for the Marginal Model.- Inference for the Random Effects.- Fitting Linear Mixed Models with SAS.- General Guidelines for Model Building.- Exploring Serial Correlation.- Local Influence for the Linear Mixed Model.- The Heterogeneity Model.- Conditional Linear Mixed Models.- Exploring Incomplete Data.- Joint Modeling of Measurements and Missingness.- Simple Missing Data Methods.- Selection Models.- Pattern-Mixture Models.- Sensitivity Analysis for Selection Models.- Sensitivity Analysis for Pattern-Mixture Models.- How Ignorable Is Missing At Random ?.- The Expectation-Maximization Algorithm.- Design Considerations.- Case Studies.
Details
Erscheinungsjahr: | 2000 |
---|---|
Fachbereich: | Wahrscheinlichkeitstheorie |
Genre: | Importe, Mathematik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Reihe: | Springer Series in Statistics |
Inhalt: |
xxii
568 S. |
ISBN-13: | 9780387950273 |
ISBN-10: | 0387950273 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: |
Molenberghs, Geert
Verbeke, Geert |
Auflage: | 1st ed. 1997. 2nd printing 2000 |
Hersteller: |
Springer New York
Springer US, New York, N.Y. Springer Series in Statistics |
Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
Maße: | 235 x 155 x 32 mm |
Von/Mit: | Geert Molenberghs (u. a.) |
Erscheinungsdatum: | 16.06.2000 |
Gewicht: | 0,89 kg |
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