Robert N. Rodriguez
Robert N. Rodriguez retired from SAS in 2018 after serving as a senior director in research and development. This book is based on his experience learning about the needs of SAS customers at user events and working with SAS/STAT developers to meet those needs. 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. He is a Fellow of the American Statistical Association and received the ASA Founders Award in 2009.
By This Author
Building Regression Models with SAS®: A Guide for Data Scientists
By Robert N. Rodriguez
Advance your skills in building predictive models with SAS!
Building Regression Models with SAS®: A Guide for Data Scientists teaches data scientists, statisticians, and other analysts who use SAS to train regression models for prediction with large, complex data. Each chapter focuses on a particular model and includes a high-level overview, followed by basic concepts, essential syntax, and examples using new procedures in both SAS/STAT and SAS Viya. By emphasizing introductory examples and interpretation of output, this book provides readers with a clear understanding of how to build the following types of models:
- general linear models
- quantile regression models
- logistic regression models
- generalized linear models
- generalized additive models
- proportional hazards regression models
- tree models
- models based on multivariate adaptive regression splines
Building Regression Models with SAS is an essential guide to learning about a variety of models that provide interpretability as well as predictive performance.
Featured Authors
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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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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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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.