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  • Format: ePub

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®…mehr

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Produktbeschreibung
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.

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Autorenporträt
Walter W. Stroup, PhD, is a professor in the Department of Statistics at the University of Nebraska-Lincoln. He teaches statistical design, analysis, and modeling. A SAS user since 1976, he is the author of three previous mixed and linear modeling books. He is a member of the Stability Shelf Life Working Group of the Product Quality Research Institute and received its Outstanding Researcher Award. He chaired Nebraska's Biometry Department from 2001 to 2003 and was founding chair of Nebraska's Statistics Department from 2003 to 2010. He is a Fellow of the American Statistical Association.