Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
EUR 143,71
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Ajouter au panierHRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.
EUR 140,30
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Ajouter au panierGebunden. Etat : New. HULIN WU, PHD, is Professor of Biostatistics in the School of Medicine and Dentistry at the University of Rochester in the Departments of Medicine Community and Preventative Medicine and Biostatistics and Computational Biology. His research interests incl.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 152,90
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Ajouter au panierEtat : New. In.
Vendeur : Anybook.com, Lincoln, Royaume-Uni
EUR 127,49
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Ajouter au panierEtat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9780471483502.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 143,70
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Ajouter au panierEtat : New.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 146,31
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Ajouter au panierEtat : New.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 154,49
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 156,17
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 169,92
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Ajouter au panierBuch. Etat : Neu. Neuware - Incorporates mixed-effects modeling techniques for more powerful and efficient methodsThis book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. The authors emphasize modeling ideas and inference methodologies, although some theoretical results for the justification of the proposed methods are presented.With its logical structure and organization, beginning with basic principles, the text develops the foundation needed to master advanced principles and applications. Following a brief overview, data examples from biomedical research studies are presented and point to the need for nonparametric regression analysis approaches. Next, the authors review mixed-effects models and nonparametric regression models, which are the two key building blocks of the proposed modeling techniques.The core section of the book consists of four chapters dedicated to the major nonparametric regression methods: local polynomial, regression spline, smoothing spline, and penalized spline. The next two chapters extend these modeling techniques to semiparametric and time varying coefficient models for longitudinal data analysis. The final chapter examines discrete longitudinal data modeling and analysis.Each chapter concludes with a summary that highlights key points and also provides bibliographic notes that point to additional sources for further study. Examples of data analysis from biomedical research are used to illustrate the methodologies contained throughout the book. Technical proofs are presented in separate appendices.With its focus on solving problems, this is an excellent textbook for upper-level undergraduate and graduate courses in longitudinal data analysis. It is also recommended as a reference for biostatisticians and other theoretical and applied research statisticians with an interest in longitudinal data analysis. Not only do readers gain an understanding of the principles of various nonparametric regression methods, but they also gain a practical understanding of how to use the methods to tackle real-world problems.
Edité par John Wiley & Sons Inc, New York, 2006
ISBN 10 : 0471483508 ISBN 13 : 9780471483502
Langue: anglais
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Edition originale
EUR 160,86
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Ajouter au panierHardcover. Etat : new. Hardcover. Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. The authors emphasize modeling ideas and inference methodologies, although some theoretical results for the justification of the proposed methods are presented. With its logical structure and organization, beginning with basic principles, the text develops the foundation needed to master advanced principles and applications. Following a brief overview, data examples from biomedical research studies are presented and point to the need for nonparametric regression analysis approaches. Next, the authors review mixed-effects models and nonparametric regression models, which are the two key building blocks of the proposed modeling techniques. The core section of the book consists of four chapters dedicated to the major nonparametric regression methods: local polynomial, regression spline, smoothing spline, and penalized spline. The next two chapters extend these modeling techniques to semiparametric and time varying coefficient models for longitudinal data analysis. The final chapter examines discrete longitudinal data modeling and analysis. Each chapter concludes with a summary that highlights key points and also provides bibliographic notes that point to additional sources for further study. Examples of data analysis from biomedical research are used to illustrate the methodologies contained throughout the book. Technical proofs are presented in separate appendices. With its focus on solving problems, this is an excellent textbook for upper-level undergraduate and graduate courses in longitudinal data analysis. It is also recommended as a reference for biostatisticians and other theoretical and applied research statisticians with an interest in longitudinal data analysis. Not only do readers gain an understanding of the principles of various nonparametric regression methods, but they also gain a practical understanding of how to use the methods to tackle real-world problems. Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Vendeur : Majestic Books, Hounslow, Royaume-Uni
EUR 185,44
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Ajouter au panierEtat : New. pp. xxii + 369 Illus.
Edité par John Wiley & Sons Inc, New York, 2006
ISBN 10 : 0471483508 ISBN 13 : 9780471483502
Langue: anglais
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Edition originale
EUR 175,29
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : new. Hardcover. Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. The authors emphasize modeling ideas and inference methodologies, although some theoretical results for the justification of the proposed methods are presented. With its logical structure and organization, beginning with basic principles, the text develops the foundation needed to master advanced principles and applications. Following a brief overview, data examples from biomedical research studies are presented and point to the need for nonparametric regression analysis approaches. Next, the authors review mixed-effects models and nonparametric regression models, which are the two key building blocks of the proposed modeling techniques. The core section of the book consists of four chapters dedicated to the major nonparametric regression methods: local polynomial, regression spline, smoothing spline, and penalized spline. The next two chapters extend these modeling techniques to semiparametric and time varying coefficient models for longitudinal data analysis. The final chapter examines discrete longitudinal data modeling and analysis. Each chapter concludes with a summary that highlights key points and also provides bibliographic notes that point to additional sources for further study. Examples of data analysis from biomedical research are used to illustrate the methodologies contained throughout the book. Technical proofs are presented in separate appendices. With its focus on solving problems, this is an excellent textbook for upper-level undergraduate and graduate courses in longitudinal data analysis. It is also recommended as a reference for biostatisticians and other theoretical and applied research statisticians with an interest in longitudinal data analysis. Not only do readers gain an understanding of the principles of various nonparametric regression methods, but they also gain a practical understanding of how to use the methods to tackle real-world problems. Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Vendeur : Books Puddle, New York, NY, Etats-Unis
EUR 201,50
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Ajouter au panierEtat : New. pp. xxii + 369.
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
EUR 145,11
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Ajouter au panierEtat : New.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 216,94
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Ajouter au panierHardcover. Etat : Brand New. 1st edition. 369 pages. 9.25x6.50x0.75 inches. In Stock.
Edité par John Wiley & Sons Inc, New York, 2006
ISBN 10 : 0471483508 ISBN 13 : 9780471483502
Langue: anglais
Vendeur : Grand Eagle Retail, Fairfield, OH, Etats-Unis
Edition originale
EUR 173,65
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Ajouter au panierHardcover. Etat : new. Hardcover. Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. The authors emphasize modeling ideas and inference methodologies, although some theoretical results for the justification of the proposed methods are presented. With its logical structure and organization, beginning with basic principles, the text develops the foundation needed to master advanced principles and applications. Following a brief overview, data examples from biomedical research studies are presented and point to the need for nonparametric regression analysis approaches. Next, the authors review mixed-effects models and nonparametric regression models, which are the two key building blocks of the proposed modeling techniques. The core section of the book consists of four chapters dedicated to the major nonparametric regression methods: local polynomial, regression spline, smoothing spline, and penalized spline. The next two chapters extend these modeling techniques to semiparametric and time varying coefficient models for longitudinal data analysis. The final chapter examines discrete longitudinal data modeling and analysis. Each chapter concludes with a summary that highlights key points and also provides bibliographic notes that point to additional sources for further study. Examples of data analysis from biomedical research are used to illustrate the methodologies contained throughout the book. Technical proofs are presented in separate appendices. With its focus on solving problems, this is an excellent textbook for upper-level undergraduate and graduate courses in longitudinal data analysis. It is also recommended as a reference for biostatisticians and other theoretical and applied research statisticians with an interest in longitudinal data analysis. Not only do readers gain an understanding of the principles of various nonparametric regression methods, but they also gain a practical understanding of how to use the methods to tackle real-world problems. Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Edité par John Wiley and Sons Ltd, 2006
ISBN 10 : 0471483508 ISBN 13 : 9780471483502
Langue: anglais
Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlande
Edition originale
EUR 241
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Ajouter au panierEtat : New. Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. Series: Wiley Series in Probability and Statistics. Num Pages: 400 pages, Illustrations. BIC Classification: MJ; PB. Category: (P) Professional & Vocational. Dimension: 166 x 241 x 28. Weight in Grams: 766. . 2006. 1st Edition. Hardcover. . . . .
Edité par John Wiley and Sons Ltd, 2006
ISBN 10 : 0471483508 ISBN 13 : 9780471483502
Langue: anglais
Vendeur : Kennys Bookstore, Olney, MD, Etats-Unis
EUR 294,55
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. Series: Wiley Series in Probability and Statistics. Num Pages: 400 pages, Illustrations. BIC Classification: MJ; PB. Category: (P) Professional & Vocational. Dimension: 166 x 241 x 28. Weight in Grams: 766. . 2006. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
EUR 177,29
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Ajouter au panierHardback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 716.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 204,94
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierHardcover. Etat : Brand New. 1st edition. 369 pages. 9.25x6.50x0.75 inches. In Stock. This item is printed on demand.