SAS Essentials A Guide to Mastering SAS for Research

ISBN-10: 0470461292

ISBN-13: 9780470461297

Edition: 2010

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Description: SAS Essentials provides an introduction to SAS statistical software, the premiere statistical data analysis tool for scientific research. Through its straightforward approach, the text presents SAS with step-by-step examples. With over fifteen years of teaching SAS courses and over fifty combined years of teaching and consulting by the authors, this valuable reference presents data manipulation and statistical techniques, including a website with examples. This textbook is essential for teachers because the chapters are self-contained and may be used accordingly to the teacherrsquo;s preference, whether for a one-semester or two-semesters course.

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Book details

List price: $82.95
Copyright year: 2010
Publisher: John Wiley & Sons, Incorporated
Publication date: 12/3/2009
Binding: Paperback
Pages: 350
Size: 7.00" wide x 9.50" long x 1.00" tall
Weight: 1.584
Language: English

Alan Elliott is the Director of the Statistical Consulting Center at Southern Methodist University within the Department of Statistical Science. Previously he served as a statistical consultant in the Department of Clinical Science at the University of Texas Southwestern Medical Center at Dallas for 30 years. Elliott holds master's degrees in Business Administration (MBA) and Applied Statistics (MAS). He has authored or coauthored over 35 scientific articles and over a dozen books including the Directory of Microcomputer Statistical Software, Microcomputing with Applications , Using Norton Utilities, SAS Essentials, Applied Time Series Analysis, and Statistical Analysis Quick reference Guidebook with SPSS Examples. Elliott has taught university-level courses in statistics, statistical consulting, and statistical computing for over twenty-five years.nbsp;

Wayne A. Woodward, Ph.D., is a Professor of Statistics and chair of the Department of Statistical Science at Southern Methodist University. He is a fellow of the American Statistical Association and was the 2004 recipient of the Don Owen award for excellence in research, statistical consulting, and service to the statistical community. In 2007 he received the Outstanding Presentation Award given by the Section on Physical and Engineering Sciences at the 2007 Joint Statistical Meetings in Salt Lake City, Utah. In 2003 he was named a Southern Methodist University Distinguished Teaching Professor by the university's Center for Teaching Excellence, and he received the 2006-2007 Scholar/Teacher of the Year Award at SMU, an award given by the United Methodist Church. . Over the last 35 years he has served as statistical consultant to a wide variety of clients in the scientific community and has taught statistics courses ranging from introductory undergraduate statistics courses to graduate courses within the Ph.D. program in Statistics at Southern Methodist University. He has been funded on numerous research grants and contracts from government and industry to study such issues as global warming and nuclear monitoring.nbsp; He has authored or coauthored over 70 scientific papers and four books.nbsp;

Preface
Getting Started
Using SAS in a Windows Environment
Your First SAS Analysis
How SAS Works
Tips and Tricks for Running SAS Programs
Summary
Exercises
Getting Data into SAS
Understanding SAS Data Sets
Understanding SAS Data Set Structure
Rules for SAS Variable Names
Understanding Three SAS Variable Types
Methods of Reading Data into SAS
Going Deeper: More Techniques for Entering Data
Summary
Exercises
Reading, Writing, and Importing Data
Working with SAS Libraries and Permanent Data Sets
Reading and Creating Permanent SAS Data Sets Using the Windows File
Name Technique
Reading Data from Permanent SAS Data Sets
Reading and Creating Permanent SAS Data Sets Using a SAS Library
Creating a SAS Library Using a Dialog Box
Importing Data from Another Program
Going Deeper: More Ways to Manage Data
Going Deeper: Importing Microsoft Excel Data Using SAS Code
Discovering the Contents of a SAS Data Set
Summary
Exercises
Preparing Data for Analysis
Labeling Variables with Explanatory Names
Creating New Variables
Using DROP and KEEP to Select Variables
Subsetting Data Sets
Using the SET Statement to Read an Existing Data Set
Using PROC SORT
Appending and Merging Data Sets
Going Deeper: Using PROC FORMAT
Summary
Exercises
Preparing to Use SAS Procedures
Understanding SAS Support Statements
Understanding PROC Statement Syntax
Using the ID Statement in a SAS Procedure
Using the LABEL Statement in a SAS Procedure
Using the WHERE Statement in a SAS Procedure
Using PROC PRINT
Going Deeper: Introducing the SAS Output Delivery System (ODS)
Summary
Exercises
Evaluating Quantitative Data
Using PROC MEANS
Using PROC UNIVARIATE
Going Deeper: Advanced PROC UNIVARIATE Options
Summary
Exercises
Analyzing Counts and Tables
Using PROC FREQ
Analyzing One-Way Frequency Tables
Creating One-Way Frequency Tables from Summarized Data
Analyzing Two-Way Tables
Going Deeper: Calculating Relative Risk Measures
Going Deeper: Inter-Rater Reliability (Kappa)
Summary
Exercises
Comparing Means Using t-tests
Performing a One-Sample t-test
Performing a Two-Sample t-test
Performing a Paired t-test
Summary
Exercises
Analysis of Variance
Comparing Three or More Means Using One-Way Analysis of Variance
Comparing Three or More Repeated Measures
Going Deeper: Graphing Mean Comparisons
Summary
Exercises
Correlation and Regression
Correlation Analysis Using PROC CORR
Simple Linear Regression
Multiple Linear Regression Using PROC REG
Going Deeper: Calculating Predictions
Going Deeper: Residual Analysis
Summary
Exercises
Nonparametric Analysis
Comparing Two Independent Samples Using NPAR1WAY
Comparing k Independent Samples (Kruskal-Wallis)
Comparing Two Dependent (Paired) Samples
Comparing k Dependent Samples (Friedman's Test)
Going Deeper: Nonparametric Multiple Comparisons
Summary
Exercises
Logistic Regression
Logistic Analysis Basics
Performing a Logistic Analysis using PROC LOGISTIC
Using Simple Logistic Analysis
Multiple Binary Logistic Analysis
Going Deeper: Assessing a Model's Fit and Predictive Ability
Summary
Exercises
Analysis of Variance
Part II Analysis of Covariance
Going Deeper: Two-Factor ANOVA Using PROC MIXED
Going Deeper: Repeated Measures with a Grouping Factor
Summary
Exercises
Creating Graphs
Creating Scatterplots and Line Graphs Using GPLOT
Creating Bar Charts and Pie Charts
Creating Stacked Bar Charts
Creating Mean Bars Using GCHART
Creating Boxplots
Going Deeper: ODS Graphics
Summary
Exercises
Controlling Output Using ODS
Specifying the ODS Output Format and Destination
Specifying ODS Output Style
Using ODS to Select Specific Output Tables for Procedures
Going Deeper: Enhancing Graphics Using ODS and Creating Hyperlinks
Going Deeper: Capturing Information from ODS Tables
Extended ODS Features
Summary
Exercises
Advanced SAS Programming Topics
Reading and Writing Data Using DDE
Using the RETAIN Statement
Arrays and DO Loops
Transposing Data Sets
Using SAS Macros
Summary
Exercises
SAS Graph Options Reference
Using SAS Fonts
Specifying SAS Color Choices
Specifying Patterns for PROCS GPLOT and PROC UNIVARIATE
Bar and Block Patterns for Bar Charts, Pie Charts, and Other Graphics
SAS Line Styles
Using SAS Plotting Symbols
SAS Function Reference
Using SAS Functions
Arithmetic/Mathematical Functions
Trignometric Functions
Date and Time Functions
Character Functions
Truncation Functions
Special Use Functions
Financial Functions
Working with Previous Observations
Miscellaneous Functions
Choosing a SAS Procedure
Descriptive Statistics
Comparison Tests
Relational Analyses (Correlation and Regression)
Quick Reference
References
Index
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