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Contents

List of Programs

Acknowledgments

Chapter 1 An Introduction to SAS

Introduction

What is SAS

Statistical Tasks Performed by SAS

The Structure of SAS Programs

SAS Data Sets

SAS Display Manager

Excel Workbooks

Variable Types in SAS Data Sets

Temporary versus Permanent SAS Data Sets

Creating a SAS Data Set from Raw Data

Data Values Separated by Delimiters

Reading CSV Files

Data Values in Fixed Columns

Excel Files with Invalid SAS Variable Names

Other Sources of Data

Conclusions

Chapter 2 Descriptive Statistics – Continuous Variables

Introduction

Computing Descriptive Statistics Using PROC MEANS

Descriptive Statistics Broken Down by a Classification Variable

Computing a 95% Confidence Interval and the Standard Error

Producing Descriptive Statistics, Histograms, and Probability Plots

Changing the Midpoint Values on the Histogram

Generating a Variety of Graphical Displays of Your Data

Displaying Multiple Box Plots for Each Value of a Categorical Variable

Conclusions

Chapter 3 Descriptive Statistics – Categorical Variables

Introduction

Computing Frequency Counts and Percentages

Computing Frequencies on a Continuous Variable

Using Formats to Group Observations

Histograms and Bar Charts

Creating a Bar Chart Using PROC SGPLOT

Using ODS to Send Output to Alternate Destinations

Creating a Cross-Tabulation Table

Changing the Order of Values in a Frequency Table

Conclusions

Chapter 4 Descriptive Statistics – Bivariate Associations

Introduction

Producing a Simple Scatter Plot Using PROG GPLOT

Producing a Scatter Plot Using PROC SGPLOT

Creating Multiple Scatter Plots on a Single Page Using PROC SGSCATTER

Conclusions

Chapter 5 Inferential Statistics – One-Sample Tests

Introduction

Conducting a One-Sample t-test Using PROC TTEST

Running PROC TTEST with ODS Graphics Turned On

Conducting a One-Sample t-test Using PROC UNIVARIATE

Testing Whether a Distribution is Normally Distributed

Tests for Other Distributions

Conclusions

Chapter 6 Inferential Statistics – Two-Sample Tests

Introduction

Conducting a Two-Sample t-test

Testing the Assumptions for a t-test

Customizing the Output from ODS Statistical Graphics

Conducting a Paired t-test

Assumption Violations

Conclusions

Chapter 7 Inferential Statistics – Comparing More than Two Means

Introduction

A Simple One-way Design

Conducting Multiple Comparison Tests

Using ODS Graphics to Produce a Diffogram

Two-way Factorial Designs

Analyzing Factorial Models with Significant Interactions

Analyzing a Randomized Block Design

Conclusions

Chapter 8 Correlation and Regression

Introduction

Producing Pearson Correlations

Generating a Correlation Matrix

Creating HTML Output with Data Tips

Generating Spearman Nonparametric Correlations

Running a Simple Linear Regression Model

Using ODS Statistical Graphics to Investigate Influential Observations

Using the Regression Equation to Do Prediction

A More Efficient Way to Compute Predicted Values

Conclusions

Chapter 9 Multiple Regression

Introduction

Fitting Multiple Regression Models

Running All Possible Regressions with n Variables

Producing Separate Plots Instead of a Panel

Choosing the Best Model (Cp and Hocking’s Criteria)

Forward, Backward, and Stepwise Selection Methods

Forcing Selected Variables into a Model

Creating Dummy (Design) Variables for Regression

Detecting Collinearity

Influential Observations in Multiple Regression Models

Conclusions

Chapter 10 Categorical Data

Introduction

Comparing Proportions

Rearranging Rows and Columns in a Table

Tables with Expected Values Less Than 5 (Fisher’s Exact Test)

Computing Chi-Square from Frequency Data

Using a Chi-Square Macro

A Short-Cut Method for Requesting Multiple Tables

Computing Coefficient Kappa—A Test of Agreement

Computing Tests for Trends

Computing Chi-Square for One-Way Tables

Conclusions

Chapter 11 Binary Logistic Regression

Introduction

Running a Logistic Regression Model with One Categorical Predictor Variable

Running a Logistic Regression Model with One Continuous Predictor Variable

Using a Format to Create a Categorical Variable from a Continuous Variable

Using a Combination of Categorical and Continuous Variables in a Logistic Regression Model

Running a Logistic Regression with Interactions

Conclusions

Chapter 12 Nonparametric Tests

Introduction

Performing a Wilcoxon Rank-Sum Test

Performing a Wilcoxon Signed-Rank Test (for Paired Data)

Performing a Kruskal-Wallis One-Way ANOVA

Comparing Spread: The Ansari-Bradley Test

Converting Data Values into Ranks

Using PROC RANK to Group Your Data Values

Conclusions

Chapter 13 Power and Sample Size

Introduction

Computing the Sample Size for an Unpaired t-Test

Computing the Power of an Unpaired t-Test

Computing Sample Size for an ANOVA Design

Computing Sample Sizes (or Power) for a Difference in Two Proportions

Using the SAS Power and Sample Size Interactive Application

Conclusions

Chapter 14 Selecting Random Samples

Introduction

Taking a Simple Random Sample

Taking a Random Sample with Replacement

Creating Replicate Samples using PROC SURVEYSELECT

Conclusions

References

Index