Linear Mixed Models for Longitudinal Data

Verbeke, Geert; Molenberghs, Geert

ISBN 10: 0387950273 / ISBN 13: 9780387950273

Editore: Springer-Verlag New York Inc., 2001

Provides a comprehensive treatment of linear mixed models for continuous longitudinal data. This book emphasises on exploratory data analysis for various aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Series: Springer Series in Statistics. Num Pages: 568 pages, 33 black & white illustrations, biography. BIC Classification: PBT; PBWH. Category: (P) Professional & Vocational. Dimension: 240 x 165 x 37. Weight in Grams: 1000. . 2001. Corrected. Hardcover. . . . . Codice articolo V9780387950273

Riassunto:

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, condional linear mid 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. How3ever, 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 Assistant Professor at the Biostistical Centre of the Katholieke Universiteit Leuven in Belgium. He received the B.S. degree in mathematics (1989) from the Katholieke Universiteit Leuven, the M.S. in biostatistics (1992) from the Limburgs Universitair Centrum, and earned a Ph.D. in biostatistics (1995) from the Katholieke Universiteit Leuven. Dr. Verbeke wrote his dissertation, as well as a number of methodological articles, on various aspects of linear mixed models for longitudinal data analysis. He has held visiting positions at the Gerontology Research Center and the Johns Hopkins University. Geert Molenberghs is Assistant Professor of Biostatistics at the Limburgs Universitair Centrum in Belgium. He received the B.S. degree in mathematics (1988) and a Ph.D. in biostatistics (1993) from the

Recensione: "This book is devoted to linear mixed-effects models with strong emphasis on the SAS procedure. Guidance and advice on practical issues are the main focus of the text. ... It is of value to applied statisticians and biomedical researchers. ... I recommend this book as a reference to applied statisticians and biomedical researchers, particularly in the pharmaceutical industry, medical and public organizations." --Wang Songgui, Zentralblatt MATH, Vol. 956, 2001

"This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Over 125 illustrations are included in the book. ... I do believe that the book may serve as a useful reference to a broader audience. Since practical examples are provided as well as discussion of the leading software utilization, it may also be appropriate as a textbook in an advanced undergraduate-level or a graduate-level course in an applied statistics program." --Ana Ivelisse Avil és, Technometrics, Vol. 43 (3), 2001

"A practical book with a great many examples, including worked computer code and access to the datasets. ... The authors state that the book covers linear mixed models for continuous outcomes ... . The book has four main strengths: its practical bent, its emphasis on exploratory analysis, its description of tools for model checking, and its treatment of dropout and missingness ... . my impression of the book was ... positive. Its strong practical nature and emphasis on dropout modelling are particularly welcome ... ." --Harry Southworth, ISCB Newsletter, June, 2002

Dati bibliografici

Titolo: Linear Mixed Models for Longitudinal Data
Casa editrice: Springer-Verlag New York Inc.
Data di pubblicazione: 2001
Legatura: Rilegato
Condizione: New