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.

SAS Institute

Building Regression Models with SAS: A Guide for Data Scientists

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