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An Intermediate Guide to SPSS Programming
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An Intermediate Guide to SPSS Programming
Using Syntax for Data Management

November 2004 | 248 pages | SAGE Publications, Inc
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An Intermediate Guide to SPSS Programming: Using Syntax for Data Management introduces the major tasks of data management and presents solutions using SPSS syntax. This book fills an important gap in the education of many students and researchers, whose coursework has left them unprepared for the data management issues that confront them when they begin to do independent research. It also serves as an introduction to SPSS programming. All the basic features of SPSS syntax are illustrated, as are many intermediate and advanced topics such as using vectors and loops, reading complex data files, and using the SPSS macro language.

An Intermediate Guide to SPSS Programming will be a welcome addition to advanced undergraduate and graduate statistics courses across the social sciences, education, and health. Professional researchers, data managers, and statisticians will also find this an invaluable reference for SPSS and data management.
 
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

“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
RMC Research Corporation

"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
St. Charles Community College

Helpful and valuable resource for any person undertaking data analysis using SPSS. Recommended for masters and doctoral research students.

Ms Kelly Maguire
Marketing Department , Leisure and Tourism, Sligo Institute of Technology
February 11, 2016
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Very few students would need this book. Would recommend to individuals as needed. Clear and helpful

Professor James Parrott
Department of Interdisciplinary Studies, University of Medicine and Dentistry of New Jersey School of Health Related Professional
March 12, 2013
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This short guide on SPSS syntax is a welcome addition to the literature and covers functions and areas that often aren't taught as part of the mainstream curriculum. Due to the advanced nature of using syntax (rather than the accessible GUI) this is really a book for postgraduates and academics.

Dr Luke Sloan
Cardiff School of Social Sciences, Cardiff University
March 7, 2011
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This is a comprehensive text book that takes the reader beyond most introductory text books but still guides them through. it is an ideal supplimentary read for Masters students and beyond, especially those who require a deeper level of syntactical understanding

Dr Paul Nash
Centre for Innovative Ageing, University of Wales, Swansea
February 2, 2011
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For those who want more advanced means in writing syntax in SPSS

Dr Nii Amoo
Department Business Studies, Bradford College
December 3, 2010
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Key features
KEY FEATURES:
  • Overview of data management issues, with practical solutions
  • A beginner-level introduction to SPSS and computer programming
  • Many examples of SPSS syntax and annotated output
  • Chapters on date and time variables in SPSS, missing data, nonstandard data files, and SPSS macro language, and random processes

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