Linear Mixed Models for Longitudinal Data (Springer Series in Statistics)

Verbeke, Geert; Molenberghs, Geert

ISBN 10: 1441902996 / ISBN 13: 9781441902993

Editore: Springer (edition 2000), 2009

Riguardo questo articolo

It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Codice articolo 1441902996-11-1

Dati bibliografici

• Titolo: Linear Mixed Models for Longitudinal Data (Springer Series in Statistics)
• Editore: Springer (edition 2000)
• Data di pubblicazione: 2009
• Lingua: Inglese
• ISBN 10: 1441902996
• ISBN 13: 9781441902993
• Rilegatura: Paperback
• Edizione: 2000.
• Condizione: Very Good

Descrizione articolo

Riassunto

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.

Dalla quarta di copertina

This paperback edition is a reprint of the 2000 edition.

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. Several variations to the conventional linear mixed model are discussed (a heterogeity model, conditional linear mixed models). This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. However, some other commercially available packages are discussed as well. Great care has been taken in presenting the data analyses in a software-independent fashion.

Geert Verbeke is Professor in Biostatistics at the Biostatistical Centre of the Katholieke Universiteit Leuven in Belgium. He is Past President of the Belgian Region of the International Biometric Society, a Board Member of the American Statistical Association, and past Joint Editor of the Journal of the Royal Statistical Society, Series A (2005--2008). He is the director of the Leuven Center for Biostatistics and statistical Bioinformatics (L-BioStat), and vice-director of the Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), a joint initiative of the Hasselt and Leuven universities in Belgium.

Geert Molenberghs is Professor of Biostatistics at Universiteit Hasselt and Katholieke Universiteit Leuven in Belgium. He was Joint Editorof Applied Statistics (2001-2004) and Co-Editor of Biometrics (2007-2009). He was President of the International Biometric Society (2004-2005), and has received the Guy Medal in Bronze from the Royal Statistical Society and the Myrto Lefkopoulou award from the Harvard School of Public Health. He is founding director of the Center for Statistics and also the director of the Interuniversity Institute for Biostatistics and statistical Bioinformatics.

Both authors have received the American Statistical Association's Excellence in Continuing Education Award in 2002, 2004, 2005, and 2008. Both are elected Fellows of the American Statistical Association and elected members of the International Statistical Institute.