An Intermediate Guide to SPSS Programming

Using Syntax for Data Management
1. Auflage 2004
ISBN: 978-0-7619-3185-0
Verlag: Sage Publications, Inc.

Buch, Englisch, 248 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 362 g

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.

Autoren/Hrsg.

Boslaugh, Sarah

Boslaugh, Sarah E.

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Prozedurale Programmierung
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software

Inhaltsverzeichnis

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

Über Autor(innen)

Boslaugh, Sarah E.
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).