Elizabeth A. Claassen
Senior Research Statistician Developer, JMP
Elizabeth A. Claassen, PhD, is a Senior Research Statistician Developer at JMP. Dr. Claassen has 9 years’ experience with SAS software and 5 years’ experience with JMP. Her chief interest is generalized linear mixed models, and she brings to this work her expertise with SAS GLM, MIXED, GLIMMIX, and NLMIXED procedures for linear models. Dr. Claassen earned an MS and PhD in statistics from the University of Nebraska–Lincoln, where she received the Holling Family Award for Teaching Excellence from the College of Agricultural Sciences and Natural Resources.
By This Author
JMP® for Mixed Models
By Ruth M. Hummel, Elizabeth A. Claassen, and Russell D. Wolfinger
JMP® for Mixed Models is a comprehensive introduction to and reference manual on the use of mixed models with JMP software. The topics covered are analysis of simple, intermediate and complex experiments using mixed model methods in JMP, specifically DOE, single and multiple random effect models, repeated measures and spatial models, random coefficient models, and power analysis. Mixed models are essential for researchers and data analysts, and JMP is the ideal visual and intuitive tool, with a unique approach to graphical statistics.
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SAS® for Mixed Models: An Introduction and Basic Applications
By Walter W. Stroup, George A. Milliken, Elizabeth A. Claassen, and Russell D. Wolfinger
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. 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.
*Our books are also available in print and e-book formats
from your local bookstore or favorite online bookseller.
Featured Authors
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Terisa Roberts is a director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, regulatory compliance, and model governance and validation. She has worked in financial services, telecommunications, government, energy, and retail sectors.
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Ron Klimberg, PhD, is a professor at the Haub School of Business at Saint Joseph's University in Philadelphia, PA.
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Robert N. Rodriguez retired from SAS in 2018 after serving as a senior director in research and development. Bob received a PhD in statistics from the University of North Carolina at Chapel Hill and was a research statistician at General Motors Research Laboratories before joining SAS.
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Todd Case has been working in the pharmaceutical industry as a statistical programmer for over 20 years. He completed his MS in Epidemiology from Columbia University and has worked at Forest Laboratories (now Allergan), Genentech, Bristol-Myers Squibb, and Biogen. He currently works at Vertex Pharmaceuticals.