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Generalized linear mixed models : = ...

Stroup, Walter W.

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Generalized linear mixed models : = modern concepts, methods and applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Generalized linear mixed models :/ Walter W. Stroup.
其他題名:	modern concepts, methods and applications /
作者:	Stroup, Walter W.
出版者:	Boca Raton :CRC Press, Taylor & Francis Group, : 2013.,
面頁冊數:	xxv, 529 p. :ill. ;27 cm.
附註:	"A Chapman & Hall book.".
標題:	Linear models (Statistics). -
ISBN:	9781439815120

Generalized linear mixed models : = modern concepts, methods and applications /
Stroup, Walter W.

Generalized linear mixed models :modern concepts, methods and applications /Walter W. Stroup. - Boca Raton :CRC Press, Taylor & Francis Group,2013. - xxv, 529 p. :ill. ;27 cm. - Chapman & Hall/CRC texts in statistical science series..

"A Chapman & Hall book.".

Includes bibliographical references (pages 513-518) and index.

Generalized Linear Mixed Models: Modern Concepts, Methods and Applications presents an introduction to linear modeling using the generalized linear mixed model (GLMM) as an overarching conceptual framework. For readers new to linear models, the book helps them see the big picture. It shows how linear models fit with the rest of the core statistics curriculum and points out the major issues that statistical modelers must consider. Along with describing common applications of GLMMs, the text introduces the essential theory and main methodology associated with linear models that accommodate random model effects and non-Gaussian data. Unlike traditional linear model textbooks that focus on normally distributed data, this one adopts a generalized mixed model approach throughout: data for linear modeling need not be normally distributed and effects may be fixed or random. With numerous examples using SAS PROC GLIMMIX, this book is ideal for graduate students in statistics, statistics professionals seeking to update their knowledge, and researchers new to the generalized linear model thought process. It focuses on data-driven processes and provides context for extending traditional linear model thinking to generalized linear mixed modeling.

ISBN: 9781439815120GBP59.99

LCCN: 2012025214Subjects--Topical Terms:

618812
Linear models (Statistics).

LC Class. No.: QA279 / .S78 2013

Dewey Class. No.: 519.5/36

Generalized linear mixed models : = modern concepts, methods and applications /
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520 # $a Generalized Linear Mixed Models: Modern Concepts, Methods and Applications presents an introduction to linear modeling using the generalized linear mixed model (GLMM) as an overarching conceptual framework. For readers new to linear models, the book helps them see the big picture. It shows how linear models fit with the rest of the core statistics curriculum and points out the major issues that statistical modelers must consider. Along with describing common applications of GLMMs, the text introduces the essential theory and main methodology associated with linear models that accommodate random model effects and non-Gaussian data. Unlike traditional linear model textbooks that focus on normally distributed data, this one adopts a generalized mixed model approach throughout: data for linear modeling need not be normally distributed and effects may be fixed or random. With numerous examples using SAS PROC GLIMMIX, this book is ideal for graduate students in statistics, statistics professionals seeking to update their knowledge, and researchers new to the generalized linear model thought process. It focuses on data-driven processes and provides context for extending traditional linear model thinking to generalized linear mixed modeling.
650 # 0 $a Linear models (Statistics). $3 618812