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SAS for mixed models /

Discover the power of mixed models with SAS. Mixed models-now the mainstream vehicle for analyzing most research data-are part of the core curriculum in most master's degree programs in statistics and data science. In a single volume, this book updates both SAS® for Linear Models, Fourth Editio...

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Bibliographic Details
Main Authors: Stroup, Walter W. (Walter Whitney), Milliken, George A., 1943- (Author), Claassen, Elizabeth A. (Author), Wolfinger, Russell Dean (Author)
Corporate Author: Safari, an O'Reilly Media Company
Format: Electronic eBook
Language:Inglés
Published: Cary, NC : SAS Institute, 2018.
Edition:First edition.
Subjects:
Online Access:Texto completo (Requiere registro previo con correo institucional)
Description
Summary:Discover the power of mixed models with SAS. Mixed models-now the mainstream vehicle for analyzing most research data-are part of the core curriculum in most master's degree programs in statistics and data science. In a single volume, this book updates both SAS® for Linear Models, Fourth Edition, and SAS® for Mixed Models, Second Edition, covering the latest capabilities for a variety of applications featuring the SAS GLIMMIX and MIXED procedures. Written for instructors of statistics, graduate students, scientists, statisticians in business or government, and other decision makers, SAS® for Mixed Models is the perfect entry for those with a background in two-way analysis of variance, regression, and intermediate-level use of SAS. This book expands coverage of mixed models for non-normal data and mixed-model-based precision and power analysis, including the following topics: Random-effect-only and random-coefficients models Multilevel, split-plot, multilocation, and repeated measures models Hierarchical models with nested random effects Analysis of covariance models Generalized linear mixed models This book is part of the SAS Press program.
Physical Description:1 online resource (608 pages) : illustrations
Bibliography:Includes bibliographical references, and index.