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Linear and generalized linear mixed ...

Jiang, Jiming.

Linear and generalized linear mixed models and their applications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Linear and generalized linear mixed models and their applicationsby Jiming Jiang, Thuan Nguyen.
Author:	Jiang, Jiming.
other author:	Nguyen, Thuan.
Published:	New York, NY :Springer New York :2021.
Description:	xiv, 343 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Linear models (Statistics)
Online resource:	https://doi.org/10.1007/978-1-0716-1282-8
ISBN:	9781071612828$q(electronic bk.)

Linear and generalized linear mixed models and their applications
Jiang, Jiming.

Linear and generalized linear mixed models and their applications[electronic resource] /by Jiming Jiang, Thuan Nguyen. - Second edition. - New York, NY :Springer New York :2021. - xiv, 343 p. :ill., digital ;24 cm. - Springer series in statistics,0172-7397. - Springer series in statistics..

1. Linear Mixed Models: Part I -- 2. Linear Mixed Models: Part II -- 3. Generalized Linear Mixed Models: Part I -- 4. Generalized Linear Mixed Models: Part II.

Now in its second edition, this book covers two major classes of mixed effects models-linear mixed models and generalized linear mixed models-and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. It offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it discusses the latest developments and methods in the field, incorporating relevant updates since publication of the first edition. These include advances in high-dimensional linear mixed models in genome-wide association studies (GWAS), advances in inference about generalized linear mixed models with crossed random effects, new methods in mixed model prediction, mixed model selection, and mixed model diagnostics. This book is suitable for students, researchers, and practitioners who are interested in using mixed models for statistical data analysis with public health applications. It is best for graduate courses in statistics, or for those who have taken a first course in mathematical statistics, are familiar with using computers for data analysis, and have a foundational background in calculus and linear algebra.

ISBN: 9781071612828$q(electronic bk.)

Standard No.: 10.1007/978-1-0716-1282-8doiSubjects--Topical Terms:

181866
Linear models (Statistics)

LC Class. No.: QA276 / .J536 2021

Dewey Class. No.: 519.535

Linear and generalized linear mixed models and their applications
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