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Ajouter au panierEtat : New. In English.
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Langue: anglais
Edité par Springer-Verlag New York Inc., US, 2013
ISBN 10 : 1461438993 ISBN 13 : 9781461438991
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Ajouter au panierHardback. Etat : New. 2013 ed.
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Ajouter au panierEtat : As New. Unread book in perfect condition.
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Ajouter au panierHardcover. Etat : Like New. Like New. book.
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Ajouter au panierEtat : New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-12 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Ajouter au panierEtat : New. pp. 576.
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Ajouter au panierBuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wide range of uses for the models by applied researchers in those and other fields by providing state-of-the-art descriptions of the implementation of LMMs in R. To help readers to get familiar with the features of the models and the details of carrying them out in R, the book includes a review of the most important theoretical concepts of the models. The presentation connects theory, software and applications. It is built up incrementally, starting with a summary of the concepts underlying simpler classes of linear models like the classical regression model, and carrying them forward to LMMs. A similar step-by-step approach is used to describe the R tools for LMMs. All the classes of linearmodels presented in the book are illustrated using real-life data. The book also introduces several novel R tools for LMMs, including new class of variance-covariance structure for random-effects, methods for influence diagnostics and for power calculations. They are included into an R package that should assist the readers in applying these and other methods presented in this text.
Langue: anglais
Edité par Springer-Verlag New York Inc., US, 2013
ISBN 10 : 1461438993 ISBN 13 : 9781461438991
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Ajouter au panierHardback. Etat : New. 2013 ed.
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Ajouter au panierHardcover. Etat : Brand New. 9th edition. 568 pages. 9.75x6.50x1.50 inches. In Stock.
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Ajouter au panierGebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a description of the most important theoretical concepts and features of linear mixed models (LMMs) and their implementation in RAll the classes of linear models presented in the book are illustrated using real-life dataP.
Langue: anglais
Edité par Springer, Humana Feb 2013, 2013
ISBN 10 : 1461438993 ISBN 13 : 9781461438991
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Ajouter au panierBuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wide range of uses for the models by applied researchers in those and other fields by providing state-of-the-art descriptions of the implementation of LMMs in R. To help readers to get familiar with the features of the models and the details of carrying them out in R, the book includes a review of the most important theoretical concepts of the models. The presentation connects theory, software and applications. It is built up incrementally, starting with a summary of the concepts underlying simpler classes of linear models like the classical regression model, and carrying them forward to LMMs. A similar step-by-step approach is used to describe the R tools for LMMs. All the classes of linearmodels presented in the book are illustrated using real-life data. The book also introduces several novel R tools for LMMs, including new class of variance-covariance structure for random-effects, methods for influence diagnostics and for power calculations. They are included into an R package that should assist the readers in applying these and other methods presented in this text. 576 pp. Englisch.
Langue: anglais
Edité par Springer-Verlag New York Inc., 2013
ISBN 10 : 1461438993 ISBN 13 : 9781461438991
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Ajouter au panierHardback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Langue: anglais
Edité par Springer, Humana Feb 2013, 2013
ISBN 10 : 1461438993 ISBN 13 : 9781461438991
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Ajouter au panierBuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wide range of uses for the models by applied researchers in those and other fields by providing state-of-the-art descriptions of the implementation of LMMs in R. To help readers to get familiar with the features of the models and the details of carrying them out in R, the book includes a review of the most important theoretical concepts of the models. The presentation connects theory, software and applications. It is built up incrementally, starting with a summary of the concepts underlying simpler classes of linear models like the classical regression model, and carrying them forward to LMMs. A similar step-by-step approach is used to describe the R tools for LMMs. All the classes of linearmodels presented in the book are illustrated using real-life data. The book also introduces several novel R tools for LMMs, including new class of variance-covariance structure for random-effects, methods for influence diagnostics and for power calculations. They are included into an R package that should assist the readers in applying these and other methods presented in this text.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 576 pp. Englisch.
Vendeur : Majestic Books, Hounslow, Royaume-Uni
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Ajouter au panierEtat : New. Print on Demand pp. 576 67 Illus.
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Ajouter au panierEtat : New. PRINT ON DEMAND pp. 576.