Isbn: 9781441924407 - correlated data analysis: modeling, analytics, and applications: modeling, analytics, and applications (springer series in statistics) (13 risultati)

Condizione: New.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Thisbook,likemanyotherbooks,wasdeliveredundertremendousinspiration and encouragement from my teachers, research collaborators, and students. My interest in longitudinal data analysis began with a short course taught jointly by K. Y. Liang and S. L. Zeger at the Statistical Society of Canada Conference in Acadia University, Nova Scotia, in the spring of 1993. At that time, I was a rst-year PhD student in the Department of Statistics at the University of British Columbia, and was eagerly seeking potential topics for my PhD dissertation. It was my curiosity (driven largely by my terrible c- fusion) with the generalized estimating equations (GEEs) introduced in the short course that attracted me to the eld of correlated data analysis. I hope that my experience in learning about it has enabled me to make this book an enjoyable intellectual journey for new researchers entering the eld. Thus, the book aims at graduate students and methodology researchers in stat- tics or biostatistics who are interested in learning the theory and methods of correlated data analysis. I have attempted to give a systematic account of regression models and their applications to the modeling and analysis of correlated data. Longitu- nal data, as an important type of correlated data, has been used as a main venue for motivation, methodological development, and illustration throu- out the book. Given the many applied books on longitudinal data analysis - ready available, this book is inclined more towards technical details regarding the underlying theory and methodology used in software-based applications.…

Condizione: New. pp. 368.

Condizione: New. In English.

Taschenbuch. Condizione: Neu. Correlated Data Analysis: Modeling, Analytics, and Applications | Peter X. -K. Song | Taschenbuch | xvi | Englisch | 2010 | Springer | EAN 9781441924407 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Paperback. Condizione: Brand New. 352 pages. 9.00x6.00x0.83 inches. In Stock.

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Condizione: new. Questo è un articolo print on demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas. 368 pp. Englisch.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. New topics are featured that have not been discussed in other books: a unified framework of model for clustered, longitudinal, or vector outcomes based on dispersion modelsA rigorous presentation of the theory of inference functions prior to the i.…

Condizione: New. Print on Demand pp. 368.

Condizione: New. PRINT ON DEMAND pp. 368.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Aimed at graduate students and researchers, this book deals with recent developments in correlated data analysis. It uses the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models, such as correlated directional data and correlated compositional data. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas and state space models for longitudinal data from long time series. Various real-world data examples, numerical illustrations and software usage tips are included too. Applied statisticians and data analysts in many subject-matter fields will find this text essential.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 368 pp. Englisch.…