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An Intermediate Guide to SPSS Programming
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Table of Contents

Preface Part I: An Introduction to SPSS 1. What Is SPSS? A Brief History of SPSS SPSS as a High-Level Programming Language SPSS as a Statistical Analysis Package 2. Interacting With SPSS The SPSS Session SPSS Windows Basics About SPSS Commands Order of Execution of SPSS Commands Batch Mode and Interactive Mode 3. Types of Files in SPSS The Command or Syntax Files The Active or Working Data File The Output Files The Journal Files 4. Customizing the SPSS Environment Displaying Current Settings Changing Current Settings Eliminating Page Breaks Increasing Memory Allocation Changing the Default Format for Numeric Variables Part II: An Introduction to Computer Programming With SPSS 5. An Introduction to Computer Programming Using Syntax Versus the Menu System The Process of Writing and Testing Syntax Typographical Conventions Used in This Book How Code and Output Are Presented in This Book Some Reasons to Use Syntax Beginning to Learn Syntax Programming Style 6. Programming Errors Syntax Errors and Logical Errors The Debugging Process Common SPSS Syntax Errors Finding Logical Errors Changing Default Error and Warning Settings Deciphering SPSS Error and Warning Messages 7. Documenting Syntax, Data, and Output Files Using Comments in SPSS Programs Using Comments to Prevent Code From Executing Documenting a Data File Echoing Text in the Output File Using Titles and Subtitles Part III: Reading and Writing Data Files in SPSS 8. Reading Raw Data in SPSS Reading Inline Data Reading External Data The FIXED, FREE, and LIST Formats Specifying the Delimiter Symbol Reading Aggregated Data With DATA LIST Reading Data With Multiple Records Per Case Using FORTRAN-Like Variable Specifications Two Shortcuts for Declaring Variables With Identical Formats Specifying Decimal Values in Data 9. Reading SPSS System and Portable Files Reading an SPSS System File Reading an SPSS Portable File Dropping, Reordering, and Renaming Variables 10. Reading Data Files Created by Other Programs Reading Microsoft Excel Files Reading Data From Earlier Versions of Excel Reading Data From Later Versions of Excel Using GET TRANSLATE to Read Other Types of Files Reading Data From Database Programs Reading SAS Data Files 11. Reading Complex Data Files Reading Mixed Data Files Reading Grouped Data Files Reading Nested Data Files Reading Data in Matrix Format 12. Saving Data Files Saving an SPSS System File Saving an SPSS Portable Data File Saving a Data File for Use by Other Programs Saving Text Files Part IV: File Manipulation and Management in SPSS 13. Inspecting a Data File Determining the Number of Cases in a File Determining What Variables Are in a File Getting More Information About the Variables Checking for Duplicate Cases Looking at Variable Values and Distributions Creating Standardized Scores 14. Combining Data Files Adding New Variables to Existing Cases Adding Summary Data to an Individual-Level File Combining Cases From Several Files Updating Values in a File 15. Data File Management Reordering and Dropping Variables in the Active File Eliminating Duplicate Records Sorting a Data Set Splitting a Data Set Selecting Cases Filtering Cases Weighting Cases 16. Restructuring Files The Unit of Analysis Changing File Structure From Univariate to Multivariate Incorporating a Test Condition When Restructuring a File Changing File Structure From Multivariate to Univariate Transposing the Rows and Columns of a Data Set 17. Missing Data in SPSS Types of Missing Data System-Missing and User-Missing Data Looking at Missing Data on Individual Variables Looking at the Pattern of User-Missing Data Among Pairs of Variables Looking at the Pattern of Missing Data Across Many Variables Changing the Value of Blanks in Numeric Fields Treatment of Missing Values in SPSS Commands Substituting Values for Missing Data 18. Using Random Processes in SPSS The Random-Number Seed Generating Random Distributions Random Selection of Cases Random Group Assignment Random Selection From Multiple Groups Part V: Variables and Variable Manipulations 19. Variables and Variable Formats String and Numeric Variables System Variables Scratch Variables Input and Output Formats The NUMBER Format The COMMA, DOT, DOLLAR, and PCT Formats 20. Variable and Value Labels Rules About Variable Names in SPSS Systems for Naming Variables Adding Variable Labels Adding Value Labels Controlling Whether Labels Are Displayed in Tables Applying the Data Dictionary From a Previous Data Set 21. Recoding and Creating Variables The IF Statement Relational Operators Logical Variables Logical Operators Creating Dummy Variables The RECODE and AUTORECODE Commands Converting Variables From Numeric to String or String to Numeric Counting Occurrences of Values Across Variables Counting the Occurrence of Multiple Values in One Variable Creating a Cumulative Variable 22. Numeric Operations and Functions Arithmetic Operations Mathematical and Statistical Functions Missing Values in Numeric Operations and Functions Domain Errors A Substring-Like Technique for Numeric Variables 23. String Functions The Substring Function Concatenation Searching for Characters Within a String Variable Adding or Removing Leading or Trailing Characters Finding Character Strings Identified by Delimiters 24. Date and Time Variables How Date and Time Variables Are Stored in SPSS An Overview of SPSS Date Formats Reading Dates With Two-Digit Years in the Correct Century Creating Date Variables With Syntax Creating Date Variables From String Variables Extracting Part of a Date Variable Doing Arithmetic With Date Variables Creating a Variable Holding Today's Date Designating Missing Values for Date Variables Part VI: Other Topics 25. Automating Tasks Within Your Program Vectors The DO IF Command Structure The DO REPEAT Command Structure The LOOP Command Structure 26. A Brief Introduction to the SPSS Macro Language The Parts of a Macro Macros Without Arguments Macros With Arguments Specifying Arguments by Position Macros Using a Flexible Number of Variables Controlling the Macro Language Environment Sources of Further Information About SPSS Macros 27. Resources for Learning More About SPSS Syntax Books Web Pages Mailing Lists References Index About the Author

About the Author

Sarah E. Boslaugh, Ph.D., M.P.H., has over 20 years of experience in statistical analysis, grant writing, and teaching; her employers and clients have included the New York City Public Schools, Montefiore Medical Center, Kennesaw State University, Washington University School of Medicine, and Saint Louis University. She served as editor-in-chief for the Encyclopedia of Epidemiology (SAGE, 2007), and has published three additional books: An Intermediate Guide to SPSS Programming: Using Syntax for Data Management (SAGE, 2004), Secondary Data Sources for Public Health: A Practical Guide (Cambridge University Press, 2007), and Statistics in a Nutshell (O'Reilly, 2nd ed., 2012). Boslaugh received her Ph.D. in measurement and evaluation from the City University of New York Graduate Center and her M.P.H. from Saint Louis University. She is currently a technical writer and editor at Saint Louis University in Missouri. She specializes in data-based articles and explaining statistical principles to the general public. Her research interests include comparative health care delivery systems, quality of life measurement, and gender and sexuality issues in health care delivery. In her spare time, she reviews films and books for PopMatters (http://www.popmatters.com) and Playback St. Louis (http://www.playbackstl.com).

Reviews

"The book makes a distinct and important contribution to the field by focusing on an important set of skills that is often only briefly touched upon (if at all) in courses or texts. SPSS users benefit from having solid familiarity with syntax coding in addition to being able to use the pull-down menus. A careful study of this book will help readers advance these important skills." -- Eric Einspruch
"Where was this manual when I was trying to learn SPSS for my dissertation after switching from MiniTab? It would have been a valuable tool to save enormous amounts of time. It is succinct and to the point." -- Wanda J. Long

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