This book is useful for people who want to learn SAS programing, and assumes the students have knowledge of multiple linear regression and one-way ANOVA models. A course in computer programing would be useful, as would familiarity of SAS near the level of Cody and Smith (Citation2006), which is useful for obtaining SAS output for some common statistical methods. There is a webpage (https://github.com/baileraj/SPiSv2) that contains code for each chapter and data. See Ng (Citation2012) for a review of the first edition. The second edition has added a chapter on text processing, and reorganized the chapter order. Some topics that are relevant for the SAS Base and Certifications exams are covered, and a nice feature is the highlighting of programing tips in gray. Good competitors include Delwiche and Slaughter (Citation2019) and Cody (Citation2018).
Chapter 1 defines statistical programing, gives tips for writing readable SAS programs, tips for debugging, and tips for finding SAS help on the internet. Chapter 2 examines how to get data into SAS, a step which often takes more time than obtaining and interpreting output. Chapter 3 describes how to add a program to the data step. For example, turn a numerical variable “weight” into a categorical variable “body class” with three categories: underweight, normal, and overweight. Conditional execution and looping are also described with the if–then–else statement and the do–loop. Operation order (e.g., exponentiating first), arrays, and functions associated with statistical distributions are also examined. Chapter 4 gives more information about entering data, such as adding observations, adding variables, merging datasets, and using PROC SQL (a structured query language). Chapter 5 discusses programing SAS macros (like functions in R). Chapter 6 considers customizing output and producing graphs with PROC SGPLOT. HTML, LaTeX, or PDF objects, such as tables, can be generated. Chapter 7 is a new chapter on processing text, for example, to build a dataset. Chapter 8 shows how to use PROC IML to program with matrices, and has a section on using SAS with R.
Southern Illinois University
References
- Cody, R. (2018), Learning SAS by Example: A Programmer’s Guide (2nd ed.), Cary, NC: SAS Institute.
- Cody, R. P., and Smith, J. K. (2006), Applied Statistics and the SAS Programming Language (5th ed.), Upper Saddle River, NJ: Pearson Prentice Hall.
- Delwiche, L. D., and Slaughter, S. J. (2019), The Little SAS Book: A Primer (6th ed.), Cary, NC: SAS Institute.
- Ng, H. K. T. (2012), “Statistical Programming in SAS by A. John Bailer,” Technometrics, 54, 411.