Statistical Programming in SAS Second Edition provides a foundation for programming to implement statistical solutions using SAS, a system that has been used to solve data analytic problems for more than 40 years. The author includes motivating examples to inspire readers to generate programming solutions. Upper-level undergraduates, beginning graduate students, and professionals involved in generating programming solutions for data-analytic problems will benefit from this book. The ideal background for a reader is some background in regression modeling and introductory experience with computer programming.
The coverage of statistical programming in the second edition includes
Getting data into the SAS system, engineering new features, and formatting variables
Writing readable and well-documented code
Structuring, implementing, and debugging programs that are well documented
Creating solutions to novel problems
Combining data sources, extracting parts of data sets, and reshaping data sets as needed for other analyses
Generating general solutions using macros
Customizing output
Producing insight-inspiring data visualizations
Parsing, processing, and analyzing text
Programming solutions using matrices and connecting to R
Processing text
Programming with matrices
Connecting SAS with R
Covering topics that are part of both base and certification exams.
1. Structuring, implementing, and debugging programs to learn about data
Statistical Programming
Learning from Constructed, Artificial Data
Good Programming Practice
SAS Program Structure
What Is a SAS Data Set?
Internally Documenting SAS Program
Basic Debugging
Getting Help
Exercises
2. Reading, Creating and Formatting Data Sets
What does a SAS Data Step do?
Reading Data from External Files
Reading CSV, Excel and TEXT files
Temporary versus Permanent Status of Data Sets
Formatting and Labeling Variables
User-defined Formatting
Recoding and Transforming Variables in a DATA Step
Writing Out a File or Making a Simple Report
Exercises
3. Programming a DATA step
Writing Programs by subdividing tasks
Ordering How Tasks are Done
Index-able Lists of variables, aka arrays
Functions associated with Statistical Distributions
Generating Variables Using Random Number Generators
Remembering Variable Values across Observations
Processing multiple observations for a single observation
Case Study 1: Is the Two-Sample t-Test Robust to Violations of the Heterogeneous Variance assumption?
Efficiency considerations – how long does it take?
Case Study 2: Monte Carlo Integration to Estimate an Integral
Case Study 3: Simple Percentile-Based Bootstrap
Case Study 4: Randomization Test for the Equality of Two Populations
Exercises
4. Combining, extracting and reshaping data
Adding observations by SET-ing data sets
Adding variables by MERGE-ing data sets
Working with tables in PROC SQL
Converting wide to long formats
Converting long to wide formats
Case Study: Reshaping a World Bank data set
Building training and validation data sets
Exercises
Self-Study lab
5. Macro Programming
What Is a Macro and Why Would You Use It?
Motivation for Macros: Numerical Integration to Determine P(0<Z<1.645)
Processing Macros
Macro Variables, Parameters, and Functions
Conditional Execution, Looping, and Macros
Saving Macros
Functions and Routines for Macros
Case Study: Macro for constructing training and test data set for Model Comparison
Case Study: Processing Multiple Data Sets
Exercises
6. Customizing Output and Generating Data Visualizations
Using the Output Delivery System
Graphics in SAS
ODS Statistical Graphics
Modifying Graphics Using the ODS Graphics Editor
Graphing with Styles and Templates
Statistical Graphics—Entering the Land of SG Procedures
Case Study: Using the SG Procedures
Enhancing SG displays – options with SG procedure statements
Using Annotate Data Sets to enhance SG displays
Using Attribute Maps to enhance SG displays
Exercises
7. Processing Text
Cleaning and Processing Text Data
Starting with Character Functions
Processing Text
Case Study: Sentiment in State of the Union addresses
Case Study: Reading Text from a Web Page
Regular Expressions
Case Study (revisited) – Applying Regular Expressions
Exercises
8. Programming with Matrices and Vectors
Defining a Matrix and Subscripting
Using Diagonal Matrices and Stacking Matrices
Using Elementwise Operations, Repeating, and Multiplying Matrices
Importing a Data Set into SAS/IML and Exporting Matrices from SAS/IML to a Data Set
Case Study 1: Monte Carlo Integration to Estimate π
Case Study 2: Bisection Root Finder
Case Study 3: Randomization Test Using Matrices Imported from PROC PLAN
Case Study 4: SAS/IML Module to Implement Monte Carlo Integration to Estimate π
Storing and loading SAS/IML modules
SAS/IML and R
Exercises
References
Biography
A. John Bailer, PhD, PStat®, is a University Distinguished Professor and a founding chair of the Department of Statistics and an affiliate member of the Departments of Biology and Sociology and Gerontology as well as the Institute for the Environment and Sustainability at the Miami University in Oxford, Ohio. He is President of the International Statistical Institute (2019–2021). He previously served on the Board of Directors of the American Statistical Association. He is a Fellow of the American Statistical Association, the Society for Risk Analysis, and the American Association for the Advancement of Science. His research has focused on the quantitative risk estimation but has collaborations addressing problems in toxicology, environmental health, and occupational safety. He received the E. Phillips Knox Distinguished Teaching Award in 2018 after previously receiving the Distinguished Teaching Award for Excellence in Graduate Instruction and Mentoring and the College of Arts and Science Distinguished Teaching Award. He is also the co-founder and continuing panelist on the Stats+Stories podcast (www.statsandstories.net).
"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.…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."
~Technometrics"This is a very complete book for programming SAS in statistical analyses. This second edition offers the possibility to debug some programs and provides new examples and applications, which are very useful. This book is a very useful companion tool for students or beginners in SAS, or for more experienced statisticians who already use SAS for statistical analyses."
~ISCB News
