Statistical Programming in SAS (Paperback, 2 ed)

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