Using SPSS Syntax: A Beginner's Guide

SPSS syntax is the command language used by SPSS to carry out all of its commands and functions. In this book, Jacqueline Collier introduces the use of syntax to those who have not used it before, or who are taking their first steps in using syntax.

Without requiring any knowledge of programming, the text outlines:

how to become familiar with the syntax commands;

how to use them throughout the data entry, management and analysis process.

Collier covers all aspects of data management from data entry through to data analysis, including managing the errors and the error messages created by SPSS. Syntax commands are clearly explained and the value of syntax is demonstrated through more than 100 examples.

This book also supports the use of SPSS syntax alongside the usual drop-down, menu-driven graphical interface (GIF), using the two methods together in a complementary way. The book enables the reader to pick and choose how much one method is relied upon over the other, encouraging them to be used side-by-side, with a gradual increase in the use of syntax as knowledge, skills and confidence develop.

Most examples in the book are based upon the SPSS sample datasets which are provided with SPSS software. You can reproduced the syntax examples yourself to see how they work and what outcomes they produce. Alternatively the syntax used in the examples can be downloaded from the companion website at sagepub.co.uk/colliersyntax to enable you to run them more easily.

This book is ideal for all those carrying out quantitative research in the health and social sciences who can benefit from SPSS syntax's capacity to save time, reduce errors and allow a data audit trail.

1117321839
Using SPSS Syntax: A Beginner's Guide

SPSS syntax is the command language used by SPSS to carry out all of its commands and functions. In this book, Jacqueline Collier introduces the use of syntax to those who have not used it before, or who are taking their first steps in using syntax.

Without requiring any knowledge of programming, the text outlines:

how to become familiar with the syntax commands;

how to use them throughout the data entry, management and analysis process.

Collier covers all aspects of data management from data entry through to data analysis, including managing the errors and the error messages created by SPSS. Syntax commands are clearly explained and the value of syntax is demonstrated through more than 100 examples.

This book also supports the use of SPSS syntax alongside the usual drop-down, menu-driven graphical interface (GIF), using the two methods together in a complementary way. The book enables the reader to pick and choose how much one method is relied upon over the other, encouraging them to be used side-by-side, with a gradual increase in the use of syntax as knowledge, skills and confidence develop.

Most examples in the book are based upon the SPSS sample datasets which are provided with SPSS software. You can reproduced the syntax examples yourself to see how they work and what outcomes they produce. Alternatively the syntax used in the examples can be downloaded from the companion website at sagepub.co.uk/colliersyntax to enable you to run them more easily.

This book is ideal for all those carrying out quantitative research in the health and social sciences who can benefit from SPSS syntax's capacity to save time, reduce errors and allow a data audit trail.

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Using SPSS Syntax: A Beginner's Guide

Using SPSS Syntax: A Beginner's Guide

by Jacqueline Collier
Using SPSS Syntax: A Beginner's Guide

Using SPSS Syntax: A Beginner's Guide

by Jacqueline Collier

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Overview

SPSS syntax is the command language used by SPSS to carry out all of its commands and functions. In this book, Jacqueline Collier introduces the use of syntax to those who have not used it before, or who are taking their first steps in using syntax.

Without requiring any knowledge of programming, the text outlines:

how to become familiar with the syntax commands;

how to use them throughout the data entry, management and analysis process.

Collier covers all aspects of data management from data entry through to data analysis, including managing the errors and the error messages created by SPSS. Syntax commands are clearly explained and the value of syntax is demonstrated through more than 100 examples.

This book also supports the use of SPSS syntax alongside the usual drop-down, menu-driven graphical interface (GIF), using the two methods together in a complementary way. The book enables the reader to pick and choose how much one method is relied upon over the other, encouraging them to be used side-by-side, with a gradual increase in the use of syntax as knowledge, skills and confidence develop.

Most examples in the book are based upon the SPSS sample datasets which are provided with SPSS software. You can reproduced the syntax examples yourself to see how they work and what outcomes they produce. Alternatively the syntax used in the examples can be downloaded from the companion website at sagepub.co.uk/colliersyntax to enable you to run them more easily.

This book is ideal for all those carrying out quantitative research in the health and social sciences who can benefit from SPSS syntax's capacity to save time, reduce errors and allow a data audit trail.


Product Details

ISBN-13: 9781412922173
Publisher: SAGE Publications
Publication date: 11/30/2009
Pages: 216
Product dimensions: 6.90(w) x 9.60(h) x 0.80(d)

Table of Contents

List of Syntax Command Examples ix

Preface xiii

Acknowledgments xiv

1 Introduction 1

Explanations and Illustrations of the Log and the Journal 2

The Journal - What it is, and How to Set the Journal Options Appropriately for Syntax Use 2

How to Set the Journal 4

The Log - What it is, and How to Set the Log Options Appropriately for Syntax Use 6

Syntax Files 8

Methods for Opening the Syntax Editor 9

Writing a Syntax File Using the Log 12

Creating a Repeat Analysis Syntax File 13

Summary 14

SPSS Conventions 16

2 Syntax for Data Entry 18

Different Methods of Data Entry in SPSS 19

Summary 28

Resources 30

3 Increasing the Usability of the Datafile 33

Variable Names 34

Labelling the Variables 36

Labelling the Values of Data in the Datafile 39

Missing Values 41

Checking the Datafile Layout and Variable Content 43

Summary 44

4 Amending the Datafile 45

Extracting to a Smaller Datafile 46

Adding New Variables to a Dataset 47

Adding New Cases to an Existing Datafile 49

Summary 52

5 Syntax Involving String Variables 53

Converting Numeric Values to Text Representations of Numbers 54

Converting Text Representations of Numbers to Numeric Values 55

Converting Categorical Text to Numeric Values 58

Date as Text into Date Format 66

Manipulating String Variables 68

Summary 70

6 Syntax Involving Date and Time Variables 83

How SPSS Works with Dates and Time 71

Date and Time Wizard 72

Setting the Date and Time Formats 74

Extracting Month, Day of Week, Year 77

Calculations Including Both Date and Time 78

Summary 81

7 Syntax for Manipulating Numeric Variables 83

Basic Principles to Observe in Transforming Data andCreating Variables 84

Advantages of Using Syntax 85

Deleting Variables 85

Routine/Simple Data Manipulation 86

Creating Categories from Continuous Numerical Data 89

Counting Data Values 92

Summary 94

8 Syntax for Data Exploration 95

Data Analysis Plans 96

Exploring Categorical Data 97

Exploring (or Describing) Numerical Data 102

Statistics to Examine the Distribution of Data 108

Summary 109

9 Syntax to Enable the Use of Only Sub-sections of the Data 111

Selecting only a Certain Part of Your Data to Be Included in the Analysis 112

Enabling the Analysis to Be Presented Separately for Certain Groups 116

Use of the TEMPORARY and SELECT IF Commands 119

Summary 122

10 Syntax for Graphs 123

Overview of Creating Graphs in SPSS 123

Templates 125

Graphs Created from Legacy Dialogs via the Interactive Option 127

Graphs Created from Legacy Dialogs via Individual Graph Type Options 131

Graphs Created from Chart Builder 136

Summary 141

11 Syntax for Univariate Analysis 143

Categorical Data 144

Ordinal Data - Differences 147

Interval Data - Differences 152

Correlations 161

Summary 164

12 Syntax for Linear and Logistic Regression Analysis 166

Linear Regression 167

Logistic Regression 171

Usefulness of Syntax 173

Summary 177

13 Understanding Error Messages and Warnings 179

Differences between Error and Warning messages 181

Summary 192

Glossary 194

References 196

Index 197

Index of Commands and Keywords 200

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