Becoming a Reviewer
Become a technical reviewer and help shape new SAS Press books. Your insight and knowledge will contribute to the process of creating cutting-edge resources for customers around the world. Plus, you'll get a firsthand look at the work of thought leaders and expert SAS users – while earning credit toward purchasing SAS books. Here's how to get started:
- Select the book you're interested in reviewing from the list below and complete all the information on the form.
- After you submit the form, your name will be forwarded to an editor. The editor will review your application and contact you if there is an opportunity for you to review the book.
- By James GearheartEnd-to-End Data Science with Base SAS would provide ALL SAS programmers a resource that would not only provide insight into the models, methodology and SAS coding required to develop machine learning models in any industry, it would also serve as a reference for any non-SAS programmer who either wants to expand their knowledge base or who has just been hired into a data scientist position where SAS is the preferred language.
- By Steve FigardThe topics will introduce them to how to think like a biostatistician with real life problems to make it relevant. This includes how to determine what tests are the most appropriate to answer the question being studied. Many of the methods are common to other disciplines, such as comparing treatment groups with t tests and ANOVA, but some topics will cover material that finds greater use in the biological sciences. These will include topics such as odds ratios and relative risk, and survival analysis. This basic knowledge of biostatistics will help the readers to both understand and evaluate what they read in the biological and medical literature as well as enable them to correctly generate and interpret such statistics from their own data.
- by Ruth Hummel, Elizabeth A. Claassen, and Russell D. WolfingerThis book will use the visual features and the other unique features of JMP to appeal to a broader data analytics audience than the SAS programming audience of SAS for Mixed Models, covering the topic of mixed models for the first time in a full JMP book. This book will be a comprehensive introduction to and reference manual on and include new features of the software. Topics will include 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.
- By Felix LiaoMost SAS Visual Analytics users today only use the most basic visualizations and charts and are only scratching the surface in terms of the tool’s full potential. These users lack basic understanding of the more advanced analytics techniques, struggle with identifying the relevant business context in which to apply these advanced techniques and are not familiar with the relevant SAS Visual Analytics components. The purpose of this book is to present these related concepts in a cohesive, simple and practical manner and equip the readers with the necessary knowledge and skill to take their data discovery to the next level using SAS Visual Analytics.
- By Paul D. Allison For graduate students taking statistics courses on structural equation modeling (SEM), for researchers with no prior knowledge of SEM who want to learn it independently, and for experienced users of SEM who want SAS know-how, this books provides a comprehensive introduction to SEM that uses SAS for all the examples. It assumes no prior knowledge of SEM, but requires that the reader have a reasonable mastery of the theory and practice of linear regression. In content, level, and tone, it resembles Allison's successful books Survival Analysis Using SAS and Logistic Regression Using SAS.
- By Paul D. Allison Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Third Edition, will be a thoroughly updated, accessible, data-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with this new edition that incorporates the many enhancements in SAS procedures for survival analysis in SAS 9.4 and covers key SAS procedures unique to SAS Viya. Topics include censoring, survival curves, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, discrete-time analysis, time-dependent covariates, competing risks, and repeated events.