Spss BASE 14.0 User Manual

SPSS Base 14.0 User’s Guide

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SPSS Base 14.0 User’s Guide

Copyright © 2005 by SPSS Inc.

All rights reserved.

Printed in the United States of America.

No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic,

mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher.

1234567890 08070605

ISBN 0-13-221804-6

SPSS 14.0

SPSS 14.0 is a comprehensive system for analyzing data. SPSS can take data from
almost any type of file and use them to generate tabulated reports, charts and plots of
distributions and trends, descriptive statistics, and complex statistical analyses.

interface of SPSS for Windows. Examples using the statistical procedures found
in SPSS Base 14.0 are provided in the Help system, installed with the software.
Algorithms used in the statistical procedures are provided in PDF form and are
available from the Help menu.

Some extended features of the system can be accessed only via command syntax.
(Those features are not available in the Student Version.) Detailed command syntax
reference information is available in two forms: integrated into the overall Help
system and as a separate document in PDF form in the SPSS 14.0 Command Syntax
Reference, also available from the Help menu.

Preface

This manual, the SPSS Base 14.0 User’s Guide, documents the graphical user

In addition, beneath the menus and dialog boxes, SPSS uses a command language.

SPSS Options

The following options are available as add-on enhancements to the full (not Student
Version) SPSS Base system:

SPSS Regression Models™ provides techniques for analyzing data that do not fit

traditional linear statistical models. It includes procedures for probit analysis,
logistic regression, weight estimation, two-stage least-squares regression, and general
nonlinear regression.

SPSS Advanced Models™ focuses on techniques oftenusedinsophisticated

experimental and biomedical research. It includes procedures for general linear models
(GLM), linear mixed models, variance components analysis, loglinear analysis,

iii

ordinal regression, actuarial life tables, Kaplan-Meier survival analysis, and basic
and extended Cox regression.

SPSS Tables™ creates a variety of presentation-quality tabular reports, including

complex stub-and-banner tables and displays of multiple-response data.

SPSS Trends™ performs comprehensive forecasting and time series analyses with

multiple curve-fitting models, smoothing models, and methods for estimating
autoregressive functions.

SPSS Categories® performs optimal scaling procedures, including correspondence

analysis.

SPSS Conjoint™ provides a realistic way to measure how individual product attributes

affect consumer and citizen preferences. With SPSS Conjoint, you can easily measure
the trade-off effect of each product attribute in the context of a set of product
attributes—as consumers do when making purchasing decisions.

SPSS Exact Tests™ calculates exact p values for statistical tests when small or very

unevenly distributed samples could make the usual tests inaccurate.

SPSS Missing Value Analysis™ describes patterns of missing data, estimates means and

other statistics, and imputes values for missing observations.

SPSS Maps™ turns your geographically distributed data into high-quality maps with

symbols, colors, bar charts, pie charts, and combinations of themes to present not only
what is happening but where it is happening.

SPSS Complex Samples™ allows survey, market, health, and public opinion researchers,

as well as social scientists who use sample survey methodology, to incorporate their
complex sample designs into data analysis.

SPSS Classification Trees™ creates a tree-based classification model. It classifies

cases into groups or predicts values of a dependent (target) variable based on values
of independent (predictor) variables. The procedure provides validation tools for
exploratory and confirmatory classification analysis.

SPSS Data Validation™ provides a quick visual snapshot of your data. It provides

the ability to apply validation rules that identify invalid data values. You can create
rules that flag out-of-range values, missing values, or blank values. You can also save
variables that r ecord individual rule violations and the total number of rule violations
per case. A limited set of predefined rules that you can copy or modify is provided.

iv

Amos™ (analysis of moment structures) uses structural equation modeling to confirm

and explain conceptual models that involve attitudes, perceptions, and other factors
that drive behavior.

The SPSS family of products also includes applications for data entry, text analysis,
classification, neural networks, and predictive enterprise services.

Installation

To install the SPSS Base system, run the License Authorization Wizard using the
authorization code that you received from SPSS Inc. For more information, see the
installation instructions supplied with the SPSS Base system.

Compatibility

SPSS is designed to run on many computer systems. See the installation instructions
that came with your system for specific information on minimum and recommended
requirements.

Serial Numbers

Your serial number is your identification number with SPSS Inc. You will need this
serial number when you contact SPSS Inc. for information regarding support, payment,
or an upgraded system. The serial number was provided with your Base system.

Customer Service

If you have any questions concerning your shipment or account, contact your local
office, listed on the SPSS Web site at http://www.spss.com/worldwide.Pleasehave
your serial number ready for identification.

Training Seminars

SPSS Inc. provides both public and onsite training seminars. All seminars feature
hands-on workshops. Seminars will be offered in major cities on a regular basis. For
more information on these seminars, contact your local office, listed on the SPSS Web
site at http://www.spss.com/worldwide.

v

Technical Support

The services of SPSS Technical Support are available to maintenance customers.
Customers may contact Technical Support for assistance in using SPSS or for
installation help for one of the supported hardware environments. To reach Technical
Support, see the SPSS Web site at http://www.spss.com, or contact your local office,
listed on the SPSS Web site at http://www.spss.com/worldwide. Be prepared to identify
yourself, your organization, and the serial number of your system.

Additional Publications

Additional copies of SPSS product manuals may be purchased dir ectly from SPSS Inc.
Visit the SPSS Web Store at http://www.spss.com/estore, or contact your local SPSS
office,listedontheSPSSWebsiteathttp://www.spss.com/worldwide. For telephone
orders in the United States and Canada, call SPSS Inc. at 800-543-2185. For telephone
orders outside of North America, contact your local office, listed on the SPSS Web site.

The SPSS Statistical Procedures Companion, by Marija Norušis, has been published

by Prentice Hall. A new version of this book, updated for SPSS 14.0, is planned.
The SPSS Advanced Statistical Procedures Companion, also based on SPSS 14.0, is
forthcoming. The SPSS Guide to Data Analysis for SPSS 14.0 is also in development.
Announcements of publications available exclusively through Prentice Hall will be
available on the SPSS Web site at http://www.spss.com/estore (select your home
country, and then click

Books).

Tell Us Your Thoughts

Your comments are important. Please let us know about your experiences with SPSS
products. We especially like to hear about new and interesting applications using the
SPSS Base system. Please send e-mail to [email protected] or write to SPSS Inc.,
Attn.: Director of Product Planning, 233 South Wacker Drive, 11th Floor, Chicago, IL
60606-6412.

About This Manual

This manual documents the graphical user interface for the procedures included in the
SPSS Base system. Illustrations of dialog boxes are taken from SPSS for Windows.
Dialog boxes in other operating systems are similar. Detailed information about the
command syntax for features in the SPSS Base system is available in two forms:

vi

integrated into the overall Help system and as a separate document in PDF form in the
SPSS 14.0 Command Syntax Reference, available from the Help menu.

Contacting SPSS

If you would like to be on our mailing list, contact one of our offices, listed on our Web
site at http://www.spss.com/worldwide.

vii

Contents

1Overview 1

What’sNewinSPSS14.0?....................................... 2

Windows .................................................... 6

Menus ...................................................... 8

StatusBar ................................................... 8

DialogBoxes ................................................. 9

VariableNamesandVariableLabelsinDialogBoxLists................. 9

DialogBoxControls........................................... 10

SubdialogBoxes.............................................. 11

SelectingVariables............................................ 11

VariableListIcons ............................................ 11

GettingInformationaboutVariablesinDialogBoxes................... 12

BasicStepsinDataAnalysis .................................... 12

StatisticsCoach.............................................. 13

FindingOutMoreaboutSPSS.................................... 13

2 Getting Help 15

UsingtheHelpTableofContents.................................. 17

UsingtheHelpIndex........................................... 18

UsingHelpSearch............................................ 19

GettingHelponDialogBoxControls............................... 20

GettingHelponOutputTerms.................................... 21

UsingCaseStudies............................................ 22

CopyingHelpTextfromaPop-UpWindow .......................... 22

ix

3 Data Files 23

OpeningaDataFile ........................................... 23

ToOpenDataFiles ............................................ 23

DataFileTypes............................................... 24

OpeningFileOptions........................................... 25

ReadingExcel5orLaterFiles.................................... 25

ReadingOlderExcelFilesandOtherSpreadsheets.................... 26

ReadingdBASEFiles .......................................... 26

ReadingStataFiles............................................ 26

ReadingDatabaseFiles ........................................ 27

TextWizard ................................................. 44

ReadingDimensionsData....................................... 55

FileInformation............................................... 59

SavingDataFiles ............................................. 60

ToSaveModifiedDataFiles..................................... 60

SavingDataFilesinExcelFormat................................. 60

SavingDataFilesinSASFormat.................................. 61

SavingDataFilesinStataFormat................................. 63

SavingDataFilesinOtherFormats................................ 64

SavingData:DataFileTypes..................................... 65

SavingSubsetsofVariables..................................... 67

SavingFileOptions............................................ 68

ProtectingOriginalData........................................ 68

VirtualActiveFile............................................. 68

4 Distributed Analysis Mode 73

DistributedAnalysisversusLocalAnalysis.......................... 73

x

5 Data Editor 85

DataView................................................... 86

VariableView................................................ 87

EnteringData................................................ 98

EditingData................................................ 100

GotoCase................................................. 103

CaseSelectionStatusintheDataEditor........................... 104

DataEditorDisplayOptions..................................... 104

DataEditorPrinting........................................... 106

6 Working with Multiple Data Sources 107

BasicHandlingofMultipleDataSources .......................... 108

CopyingandPastingInformationbetweenDatasets.................. 110

RenamingDatasets........................................... 110

7 Data Preparation 111

VariableProperties........................................... 111

DefiningVariableProperties.................................... 112

MultipleResponseSets ....................................... 119

CopyingDataProperties....................................... 122

IdentifyingDuplicateCases .................................... 132

VisualBander............................................... 135

xi

8 Data Transformations 145

ComputingVariables.......................................... 145

Functions.................................................. 148

MissingValuesinFunctions.................................... 149

RandomNumberGenerators ................................... 149

CountOccurrencesofValueswithinCases......................... 150

RecodingValues............................................. 153

RecodeintoSameVariables.................................... 153

RecodeintoDifferentVariables ................................. 155

RankCases................................................. 158

AutomaticRecode........................................... 162

DateandTimeWizard......................................... 165

TimeSeriesDataTransformations................................ 180

ScoringDatawithPredictiveModels ............................. 187

9 File Handling and File Transformations 193

SortCases ................................................. 193

Transpose.................................................. 194

MergingDataFiles........................................... 195

AddCases ................................................. 196

AddVariables............................................... 200

AggregateData............................................. 203

SplitFile................................................... 207

SelectCases ............................................... 209

WeightCases............................................... 213

RestructuringData........................................... 215

xii

10 Working with Output 239

Viewer.................................................... 239

UsingOutputinOtherApplications............................... 247

PastingObjectsintotheViewer................................. 250

PasteSpecial............................................... 250

PastingObjectsfromOtherApplicationsintotheViewer............... 251

ExportOutput............................................... 251

ViewerPrinting.............................................. 261

SavingOutput............................................... 268

11 Draft Viewer 271

ToCreateDraftOutput ........................................ 272

Controlling Draft Output Format. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273

FontsinDraftOutput.......................................... 278

ToPrintDraftOutput.......................................... 278

ToSaveDraftViewerOutput.................................... 279

12 Pivot Tables 281

ManipulatingaPivotTable..................................... 281

WorkingwithLayers.......................................... 286

Bookmarks................................................. 289

ShowingandHidingCells...................................... 290

EditingResults.............................................. 292

ChangingtheAppearanceofTables.............................. 292

TableProperties............................................. 295

xiii

ToChangePivotTableProperties................................ 295

TableProperties:General...................................... 295

TableProperties:Footnotes.................................... 296

TableProperties:CellFormats .................................. 297

TableProperties:Borders...................................... 299

TableProperties:Printing...................................... 301

Font ...................................................... 301

DataCellWidths............................................. 302

CellProperties.............................................. 304

CellProperties:Value......................................... 304

CellProperties:Alignment..................................... 306

CellProperties:Margins....................................... 307

CellProperties:Shading....................................... 307

FootnoteMarker............................................. 308

SelectingRowsandColumnsinPivotTables........................ 309

ToSelectaRoworColumninaPivotTable......................... 309

ModifyingPivotTableResults................................... 310

PrintingPivotTables.......................................... 311

ToPrintHiddenLayersofaPivotTable............................ 311

Controlling Table Breaks for Wide and Long Tables. . . . . . . . . . . . . . . . . . . 311

13 Working with Command Syntax 313

SyntaxRules................................................ 313

PastingSyntaxfromDialogBoxes ............................... 315

CopyingSyntaxfromtheOutputLog.............................. 316

EditingSyntaxinaJournalFile.................................. 318

ToRunCommandSyntax....................................... 319

MultipleExecuteCommands.................................... 320

xiv

14 Frequencies 321

FrequenciesStatistics ........................................ 323

FrequenciesCharts........................................... 325

FrequenciesFormat.......................................... 326

15 Descriptives 327

DescriptivesOptions.......................................... 329

DESCRIPTIVESCommandAdditionalFeatures ...................... 330

16 Explore 331

ExploreStatistics............................................ 334

ExplorePlots ............................................... 335

ExploreOptions ............................................. 337

EXAMINECommandAdditionalFeatures .......................... 337

17 Crosstabs 339

CrosstabsLayers ............................................ 341

CrosstabsClusteredBarCharts................................. 342

CrosstabsStatistics .......................................... 342

CrosstabsCellDisplay ........................................ 345

CrosstabsTableFormat ....................................... 347

xv

18 Summarize 349

SummarizeOptions........................................... 351

SummarizeStatistics ......................................... 352

19 Means 355

MeansOptions.............................................. 358

20 OLAP Cubes 361

OLAPCubesStatistics ........................................ 364

OLAPCubesDifferences....................................... 367

OLAPCubesTitle ............................................ 368

21 T Tests 369

Independent-SamplesTTest.................................... 369

Paired-SamplesTTest........................................ 373

One-SampleTTest........................................... 376

T-TESTCommandAdditionalFeatures............................. 378

22 One-Way ANOVA 379

One-WayANOVAContrasts.................................... 382

One-WayANOVAPostHocTests................................ 383

xvi

One-WayANOVAOptions...................................... 385

ONEWAYCommandAdditionalFeatures........................... 386

23 GLM Univariate Analysis 389

GLMModel................................................. 393

GLMContrasts.............................................. 395

GLMProfilePlots............................................ 397

GLMPostHocComparisons.................................... 398

GLMSave.................................................. 401

GLMOptions................................................ 403

UNIANOVACommandAdditionalFeatures......................... 404

24 Bivariate Correlations 407

BivariateCorrelationsOptions .................................. 410

CORRELATIONS and NONPAR CORR Command Add ition al Features . . . . . . 411

25 Partial Correlations 413

PartialCorrelationsOptions .................................... 416

PARTIALCORRCommandAdditionalFeatures ...................... 416

26 Distances 419

DistancesDissimilarityMeasures................................ 421

xvii

DistancesSimilarityMeasures.................................. 422

PROXIMITIESCommandAdditionalFeatures ....................... 423

27 Linear Regression 425

LinearRegressionVariableSelectionMethods...................... 430

LinearRegressionSetRule..................................... 431

LinearRegressionPlots ....................................... 431

LinearRegression:SavingNewVariables.......................... 433

LinearRegressionStatistics.................................... 436

LinearRegressionOptions ..................................... 438

REGRESSIONCommandAdditionalFeatures........................ 439

28 Curve Estimation 441

CurveEstimationModels ...................................... 445

CurveEstimationSave ........................................ 446

29 Discriminant Analysis 447

DiscriminantAnalysisDefineRange.............................. 450

DiscriminantAnalysisSelectCases .............................. 450

DiscriminantAnalysisStatistics................................. 451

DiscriminantAnalysisStepwiseMethod........................... 452

DiscriminantAnalysisClassification.............................. 454

DiscriminantAnalysisSave..................................... 455

DISCRIMINANTCommandAdditionalFeatures...................... 456

xviii

30 Factor Analysis 457

FactorAnalysisSelectCases................................... 462

FactorAnalysisDescriptives.................................... 462

FactorAnalysisExtraction ..................................... 463

FactorAnalysisRotation....................................... 465

FactorAnalysisScores........................................ 466

FactorAnalysisOptions ....................................... 467

FACTORCommandAdditionalFeatures............................ 468

31 Choosing a Procedure for Clustering 469

32 TwoStep C luster Analysis 471

TwoStepClusterAnalysisOptions................................ 475

TwoStepClusterAnalysisPlots.................................. 477

TwoStepClusterAnalysisOutput ................................ 479

33 Hierarchical Cluster Analysis 481

HierarchicalClusterAnalysisMethod............................. 484

HierarchicalClusterAnalysisStatistics............................ 485

HierarchicalClusterAnalysisPlots............................... 486

HierarchicalClusterAnalysisSaveNewVariables................... 487

CLUSTERCommandSyntaxAdditionalFeatures..................... 487

xix

34 K-Means Cluster Analysis 489

K-MeansClusterAnalysisEfficiency.............................. 493

K-MeansClusterAnalysisIterate................................ 494

K-MeansClusterAnalysisSave ................................. 495

K-MeansClusterAnalysisOptions ............................... 495

QUICKCLUSTERCommandAdditionalFeatures..................... 496

35 Nonparametric Tests 497

Chi-SquareTest............................................. 498

BinomialTest............................................... 502

RunsTest.................................................. 505

One-SampleKolmogorov-SmirnovTest............................ 508

Two-Independent-SamplesTests ................................ 511

Two-Related-SamplesTests.................................... 515

TestsforSeveralIndependentSamples ........................... 519

TestsforSeveralRelatedSamples ............................... 522

36 Multiple Response Analysis 527

MultipleResponseDefineSets.................................. 528

MultipleResponseFrequencies ................................. 529

MultipleResponseCrosstabs................................... 532

MultipleResponseCrosstabsDefineRanges....................... 534

MultipleResponseCrosstabsOptions............................. 534

MULTRESPONSECommandAdditionalFeatures .................... 535

xx

37 Reporting Results 537

ReportSummariesinRows..................................... 537

ReportSummariesinColumns .................................. 545

REPORTCommandAdditionalFeatures............................ 551

38 Reliability Analysis 553

Reliability An alysis Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 555

RELIABILITYCommandAdditionalFeatures ........................ 557

39 Multidimensional Scaling 559

MultidimensionalScalingShapeofData........................... 561

MultidimensionalScalingCreateMeasure......................... 562

MultidimensionalScalingModel................................. 563

MultidimensionalScalingOptions................................ 564

ALSCALCommandAdditionalFeatures............................ 564

40 Ratio Statistics 567

RatioStatistics.............................................. 569

41 Overview of the Chart Facility 571

CreatingandModifyingaChart.................................. 571

xxi

ChartDefinitionOptions....................................... 578

42 ROC Curves 585

ROCCurveOptions........................................... 588

43 Utilities 589

VariableInformation.......................................... 589

DataFileComments .......................................... 590

VariableSets ............................................... 591

DefineVariableSets.......................................... 591

UseSets................................................... 592

ReorderingTargetVariableLists................................. 593

44 Options 595

GeneralOptions............................................. 596

ViewerOptions.............................................. 598

DraftViewerOptions ......................................... 599

OutputLabelOptions ......................................... 601

ChartOptions............................................... 603

InteractiveChartOptions ...................................... 607

PivotTableOptions........................................... 608

DataOptions................................................ 610

CurrencyOptions............................................ 611

ScriptOptions............................................... 613

xxii

45 Customizing Menus and Toolbars 615

MenuEditor................................................ 615

CustomizingToolbars......................................... 616

ShowToolbars.............................................. 616

ToCustomizeToolbars ........................................ 617

46 Production Facility 623

Using the Production Facility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625

ExportOptions .............................................. 625

UserPrompts............................................... 628

ProductionMacroPrompting................................... 630

ProductionOptions........................................... 630

FormatControlforProductionJobs............................... 631

RunningProductionJobsfromaCommandLine..................... 634

PublishtoWeb.............................................. 635

SmartViewerWebServerLogin ................................. 636

47 SPSS Scripting Facility 637

ToRunaScript.............................................. 637

ScriptsIncludedwithSPSS .................................... 638

Autoscripts................................................. 639

CreatingandEditingScripts.................................... 640

ToEditaScript.............................................. 641

ScriptWindow.............................................. 642

StarterScripts.............................................. 644

xxiii

CreatingAutoscripts.......................................... 646

HowScriptsWork............................................ 649

TableofObjectClassesandNamingConventions.................... 652

NewProcedure(Scripting)..................................... 657

AddingaDescriptiontoaScript................................. 659

ScriptingCustomDialogBoxes.................................. 659

DebuggingScripts ........................................... 664

ScriptFilesandSyntaxFiles.................................... 666

48 Output Management System 669

OutputObjectTypes.......................................... 673

CommandIdentifiersandTableSubtypes.......................... 675

Labels..................................................... 676

OMSOptions............................................... 677

Logging ................................................... 682

ExcludingOutputDisplayfromtheViewer.......................... 683

RoutingOutputtoSPSSDataFiles ............................... 683

OXMLTableStructure......................................... 692

OMSIdentifiers ............................................. 697

xxiv

Appendices

A Database Access Administrator 701

B Customizing HTML Documents 703

To Add Customized HTML Code to Exported Output Docum ents . . . . . . . . . 703

ContentandFormatoftheTextFileforCustomizedHTML.............. 703

ToUseaDifferentFileorLocationforCustomHTMLCode............. 704

Index 707

xxv

Overview

SPSS for Windows provides a powerful statistical-analysis and data-management
system in a graphical environment, using descriptive menus and simple dialog boxes
to do most of the work for you. Most tasks can be accomplished simply by pointing
and clicking the mouse.

In addition to the simple point-and-click interface for statistical analysis, SPSS for
Windows provides:

Data Editor. The Data Editor is a versatile spreadsheet-like system for defining,

entering, editing, and displaying data.

Viewer. The Viewer makes it easy to browse your results, selectively show and hide

output, change the display order results, and move presentation-quality tables and
charts between SPSS and other applications.

Chapter

1

Multidimensional pivot t ables. Your results come alive with multidimensional pivot

tables. Explore your tables by rearranging rows, columns, and layers. Uncover
important findings that can get lost in standard reports. Compare groups easily by
splitting your table so that only one group is displayed at a time.

High-resolut

scatterplots, 3-D graphics, and more are included as standard features in SPSS.

Database access. Retrieve information from databases by using the Database Wizard

instead of complicated SQL queries.

Data transformations. Transformation features help get your data ready for analysis.

You can easily subset data; combine categories; add, aggregate, merge, split, and
transpose files; and more.

Electronic distrib ution. Send e-mail reports to other people with the click of a button, or

export tables and charts in HTML format for Internet and intranet distribution.

ion graphics.

High-resolution, full-color pie charts, bar charts, histograms,

1

2

Chapter 1

Online Help. Detailed tutorials provide a comprehensive overview; context-sensitive

Help topics in dialog boxes guide you through specific tasks; pop-up definitions in
pivot table results explain statistical terms; the Statistics Coach helps you find the
procedures that you need; Case Studies provide hands-on examples of how to use
statistical procedures and interpret the results.

Command language. Although most tasks can be accomplished with simple

point-and-click gestures, SPSS also provides a powerful command language that
allowsyoutosaveandautomatemanycommon tasks. The command language also
provides some functionality that is not found in the menus and dialog boxes.

Complete command syntax documentation is integrated into the overall Help system

and is available as a separate PDF document, SPSS Command Syntax Reference,which
is also available from the Help menu.

What’s New in SPSS 14.0?

Data Management

 Have multiple data sources open at the same time, making it easier to compare data

files, copy data and attributes from one file to another file, and merge multiple data
sources without saving each data source as a sorted SPSS data file first.

 Read and write Stata-format data files. You can read Stata version 4–8 data files

and write Stata version 5–8 data files. For more information, type
Index tab of the Help system.

 Read data from SPSS Dimensions data sources, including Quanvert, Quancept,

and mrInterview. For more information, see “Reading Dimensions Data” in
Chapter 3 on p. 55.

 Read data from OLE DB data sources. For more information, see “Selecting a

Data Source” in Chapter 3 on p. 28.

 Define descriptive value labels up to 120 bytes (previous limit was 60 bytes).

 Create data values f rom value labels or use them in transformation logic with the

VALUELABEL function.

 Find and replace string values with the REPLACE function.

 Define custom variable attributes and data file attributes with the VARIABLE

ATTRIBUTE and DATAFILE ATTRIBUTE commands.

Stata in the

Overview

Write data to database tables and other formats by using field/column names that



are not constrained by SPSS variable-naming rules.

SAVE TRANSLATE has been

enhanced to allow you to use quoted values for field/column names that contain
spaces, commas, or other characters that are not allowed in SPSS variable names.

 Use the new SQL subcommand of the SAVE TRANSLATE command to append new

columns to database tables, modify database table column attributes, join tables,
and perform other actions that are permitted with valid SQL statements.

Charts

 Use the new Chart Builder interface (Graphs menu) to build charts from predefined

gallery charts or from the individual parts (for example, coordinate systems and
bars) that make u p a chart.

 Create custom chart types by using powerful GGRAPH and GPL command syntax.

Statistical Enhancements

 New Expert Modeler in the Trends option automatically identifies and estimates

the best-fitting model for one or more time series, thus eliminating the need
to identify an appropriate model through trial and error. The Expert Modeler is
accessible from the Time Series Modeler dialog box or through command syntax
(with the

 New Data Validation option provides a quick visual snapshot of your data and

TSMODEL command).

provides the ability to apply validation rules that identify invalid data values.
You can create rules that flag out-of-range values, missing values, or blank
values. You can also save variables that record individual rule violations and
the total number of rule violations per case. A limited set of predefined rules is
provided that you can copy or modify. Data Validation is available through the
Validate Data dialog box on the Data menu or through command syntax (with the

VALIDATEDATA command).

New Anomaly Detection procedure in the Data Validation option finds unusual
observations that could adversely affect predictive models. Some of these outlying
observations represent truly unique cases and are thus unsuitable for prediction,
while other observations are caused by data-entry errors in which the values are
technically “correct” and thus cannot be caught by the Validate Data procedure.
Anomaly Detection is available through the Identify Unusual Cases dialog box on
the Data menu or through command syntax (with the

DETECTANOMALY command).

3

4

Chapter 1

New Multidimensional Unfolding procedure (PREFSCAL) in the Categories option



attempts to find the structure in a set of proximity measures between row and
column objects. This process is accomplished by assigning observations to specific
locations in a conceptual low-dimensional space such that the distances between
points in the space match the given (dis)similarities as closely as possible. The
result is a least-squares representation of the objects in that low-dimensional space,
which, in many cases, helps you further understand your data. This procedure is
currently available with

 New Predictor Selection procedure (SELECTPRED) in SPSS Server sifts through

PREFSCAL command syntax.

a very large number of categorical and continuous predictor variables. The
procedure selects a smaller subset for use in predictive modeling procedures that
cannot accept so many predictors. This procedure is currently available with

SELECTPRED command syntax.

 New Naïve Bayes procedure (NAIVEBAYES) in SPSS Server produces a simple and

stable model for predictor selection and classification. This procedure is currently
available with

 Improved significance testing capabilities in the Tables option allows you to now

NAIVEBAYES command syntax.

perform significance tests on subtotals and multiple response sets.

 More flexibility is available in defining multiple response sets for multiple

dichotomies.

Output

 Pivot table output is now provided for Rank Cases (RANK), Replace Missing Values

RMV), and Create Time Series (CREATE) in the Base system; all procedures in

(
the Conjoint option; Model Selection Loglinear Analysis (
the Advanced Models option; and Probit Analysis (

WLS), and 2-Stage Least Squares (2SLS) in the Regression Models option.

(

Performance Enhancements

 Table structures that previously took a long time to create or that might run out of

memory with the Custom Tables option (

CTABLES) can now be created quickly

PROBIT), Weight Estimation

HILOGLINEAR)in

and efficiently.

Enhanced Look and Fee l

 Improved variable icons that provide more at-a-glance information about variables,

including measurement level (nominal, ordinal, scale) and data type (string,
numeric, date, time).

 Full support exists for Windows XP appearance and theme settings.

SPSS 14.0 Compatibility with P revious Releases

ANY and RANGE Functions

In previous releases, the ANY and RANGE functions only returned a missing value if the
first argument resolved to a missing value. For consistency with other functions and
computations, these functions will also return a missing value if any of the remaining
arguments are system-missing or user-missing and the value of the first argument
doesn’t match any of the other non-missing arguments. So:

COMPUTE newvar=ANY(var1, var2, var3)

is now functionally equivalent to:

5

Overview

COMPUTE newvar=(var1=var2 or var1=var3).

Logistic Regression

In previous versions of SPSS, the order of recoded string values was dependent on the
order of values in the data file; for example, when recoding the dependent variable, the
first string value that was encountered was recoded to 0, and the second string value
that was encountered was recoded to 1. The procedure now recodes string variables
so that the order of recoded values is the alphanumeric order of the string values.
Thus, the procedure may recode string variables differently than in previous versions.
Logistic Regression is available in the Regression Models option.

Macro Facility

Improvements to the macro facility may cause errors in jobs that previously ran without
errors. Specifically, for syntax that is processed with interactive rules, if a macro call
occurs at the end of a command, and there is no command terminator (either a period
or a blank line), the next command after the macro expansion will be interpreted as a
continuation line instead of a new command, as in:

DEFINE !macro1()

6

Chapter 1

var1 var2 var3
!ENDDEFINE.
FREQUENCIES VARIABLES = !macro1
DESCRIPTIVES VARIABLES = !macro1.

In interactive mode, the DESCRIPTIVES command will be interpreted as a continuation
of the FREQUENCIES command, and neither command will run.

Windows

There are a number of different types of windows in SPSS:

Data Ed itor. The Data Editor displays the contents of the data file. Y

ou can create new
data files or modify existing data files with the Data Editor. If you have more than one
data file open, there is a separate Data Editor window for each data file.

Viewer. All statistical results, tables, and charts are displayed in the Viewer. You can

edit the output and save it for later use. A Viewer window opens automatically the first
time you run a procedure that generates output.

Draft Viewer. In the Draft Viewer, you can display output as simple text (instead of

interactive pivot tables).

Pivot Table Editor. Output that is displayed in pivot tables can be modified in many ways

with the Pivot Table Editor. You can edit text, swap data in rows and columns, add
color, create multidimensional tables, and selectively hide and show results.

Chart Editor. You can modify high-resolution charts and plots in chart windows. You

can change the colors, select different type fonts or sizes, switch the horizontal and
vertical axes, rotate 3-D scatterplots, and even change the chart type.

Text Output Editor. Text output that is not displayed in pivot tables can be modified

with the Text Output Editor. You can edit the output and change font characteristics
(type, style, color, size).

Syntax Editor. You can paste your dialog box choices into a syntax window, where your

selections appear in the form of command syntax. You can then edit the command
syntax to use special features of SPSS that are not available through dialog boxes. You
can save these commands in a file for use in subsequent SPSS sessions.

Script Editor. Scripting and OLE automation allow you to customize and automate

many tasks in SPSS. Use the Script Editor to create and modify basic scripts.

Figure 1-1

Data Editor and Viewer

7

Overview

Designated Window versus Active Window

If you have more than one open Viewer window, output is routed to the designated
Viewer window. If you have more than one open Syntax Editor window, command
syntax is pasted into the designated Syntax Editor window. The designated windows
are indicated by a plus sign in the icon in the title bar. You can change the designated
windows at any time.

The designated window should not be confused with the active window, which is
the currently selected window. If you have overlapping windows, the active window
appears in the foreground. If you open a window, that window automatically becomes
the active window and the designated window.

8

Chapter 1

Changing the Designated Window

E Make the window that you want to designate the active window (click anywhere in

the win dow).

E Click the Designate Window button on the toolbar (the plus sign icon).

or

E From the menus choose:

Utilities

Designate Window

Note: For Data Editor windows, the active Data Editor window determines the dataset
that is used in subsequent calculations or analyses. There is no “designated” Data
Editor window. For more information, see “Basic Handling of Multiple Data Sources”
in Chapter 6 on p. 108.

Menus

Many of the tasks that you want to p erform with SPSS are available through menu
selections. Each window in SPSS has its own menu bar with menu selections that are
appropriate for that window type.

The Analyze and Graphs menus are available in all windows, making it easy t o

generate new output without having to switch windows.

Status Bar

The status bar at the bottom of each SPSS window provides the following information:

Command status. For each procedure or command that you run, a case counter indicates

the number of cases processed so far. For statistical procedures that require iterative
processing, the number of iterations is displayed.

Filter status. If you have selected a random sample or a subset of cases for analysis, the

message
not all cases in the data file are included in the analysis.

Weight status. The message Weight on indicates that a weight variable is being used to

weight cases for analysis.

Filter on indicates that some type of case filtering is currently in effect and

Split File status. The message Split File on indicates that the data file has been split into

separate groups for analysis, based on the values of one or more grouping variables.

Showing and Hiding the Status Bar

E From the menus choose:

View

Status Bar

Dialog Boxes

Most menu selections open dialog boxes. You u se dialog boxes to select variables
and options for analysis.

Dialog boxes for statistical procedures and charts typically have two basic components:

Source variable list. A list of variables in the active dataset. O nly variable types that are

allowed by the selected procedure are displayed in the source list. Use of short string
and long string variables is restricted in many procedures.

9

Overview

Target variable list(s). One or more lists indicating the variables that you have chosen

for the analysis, such as dependent and independent variable lists.

Variable Names and Variable Labels in Dialog Box Lists

You can display either variable names or variable labels in dialog box lists.

 To control the display of variable names or labels, choose Options from the Edit

menu in any window.

 To define or modify variable labels, use Variable View in the Data Editor.

 For data that are imported from database sources, field names are used a s variable

labels.

 For long labels, position the mouse pointer over the label in the list to view the

entire label.

 If no variable label is defined, the variable name is displayed.

10

Chapter 1

Figure 1-2

Variable labels displayed in a dialog box

Dialog Box Controls

There are five standard controls in most dialog boxes:

OK. Runs the procedure. After you select your variables and choose any additional

specifica

tions, click

OK to run the procedure and close the dialog box.

Paste. Generates command syntax from the dialog box selections and pastes the syntax

into a syntax window. You can then customize the commands with additional features
that are no

Reset. Deselects any variables in the selected variable list(s) and resets all specifications

t available from dialog boxes.

in the dialog box and any subdialog boxes to the default state.

Cancel. Ca

ncels any changes that were made in the dialog box settings since the last
time it was opened and closes the dialog box. Within a session, dialog box settings are
persistent. A dialog box retains your last set of specifications until you override them.

Help. Pro

vides context-sensitive Help. This control takes you to a Help window that
contains information about the current dialog box. You can also get help on individual
dialog box controls by right-clicking the control.

Subdialog Boxes

Because most procedures provide a great deal of flexibility, not all of the possible
choices can be contained in a single dialog box. The main dialog box usually contains
the minimum information that is required to run a procedure. Additional specifications
are made in subdialog boxes.

Inthemaindialogbox,controlswithanellipsis (...) after the name indicate that a

subdialog box will be displayed.

Selecting Variables

To select a single variable, simply highlight it on the source variable list and click the
right arrow button next to the target variable list. If there is only one target variable
list, you can double-click individual variables to move them from the source list to
the target list.

You can also select multiple variables:

 To select multiple variables that are grouped together on the variable list, click the

first variable and then Shift-click the last variable in the group.

 To select multiple variables that are not grouped together on the variable list, click

the first variable, then Ctrl-click the next variable, and so on.

11

Overview

Variable List Icons

The icons that are displayed next to variables in dialog box lists provide information
about the variable type and measurement level.

Level

Scale n/a

Ordinal

Nominal

Data TypeMeasurement

Numeric String Date Time

12

Chapter 1

Getting Information about Variables in Dialog Boxes

E Right-click a variable in the source or target variable list.

E Choose Variable Information.

Figure 1-3

Variable information

Basic Steps in Data Analysis

Analyzing data with SPSS is easy. All you have to do is:

Get your data into SPSS. You can open a previously saved SPSS data file, you can

read a spreadsheet, dat
theDataEditor.

Select a procedure. Select a procedure from the menus to calculate statistics or to

create a chart.

Select the variables for the analysis. The variables in the data file are displayed in

a dialog box for the procedure.

Run the procedure and look at the results. Results are displayed in the Viewer.

abase, or text data file, or you can enter your data directly in

Statistics Coach

If you are unfamiliar with SPSS or with the statistical procedures that are available
in SPSS, the Statistics Coach can help you get started by prompting you with simple
questions, nontechnical language, and visual examples that help you select the basic
statistical and charting features that are best suited for your data.

To use the Statistics Coach, from the menus i n any SPSS window choose:

Help

Statistics Coach

The Statistics Coach covers only a selected subset of procedures in the SPSS Base
system. It is designed to provide general assistance for many of the basic, commonly
used statistical techniques.

Finding Out More about SPSS

For a comprehensive overview of SPSS basics, see the online tutorial. From any SPSS
menu choose:

Help

Tu to r i al

13

Overview

Getting Help

Help is provided in many different forms:

Help menu. The Help menu in most SPSS windows provides access to the main Help

system, plus tutorials and technical reference material.

 Topics. Provides access to the Contents, Index, and Search tabs, which you can

usetofindspecificHelptopics.

 Tutorial. Illustrated, step-by-step instructions on how to use many of the basic

features in SPSS. You don’t have to view the whole tutorial from start to finish.
You can choose the topics you want to view, skip around and view topics in any
order, and use the index or table of contents to find specific topics.

 Case Studies. Hands-on examples of how to create various types of statistical

analyses and how to interpret the results. The sample data files used in the
examples are also provided so that you can work through the examples to see
exactly how the results were produced. You can choose the specific procedure(s)
thatyouwanttolearnaboutfromthetableof contents or search for relevant topics
in the index.

 Statistics Coach. A wizard-like approach to guide you through the process of

finding the procedure that you want to use. After you make a series of selections,
the Statistics Coach opens the dialog box f or the statistical, reporting, or charting
procedure that meets your selected criteria. The Statistics Coach provides access
to most statistical and reporting procedures in the Base system and many charting
procedures.

Chapter

2

15

16

Chapter 2

Command Syntax Reference. Detailed command syntax reference information is



available in two forms: integrated into the overall Help system and as a separate
document in PDF form in the SPSS Command Syntax Reference, available from
the Help menu.

 Statistical Algorithms. The algorithms used for most statistical procedures are

available in PDF form from the Help menu and from the Help topics for the
associated dialog box interface.

Context-sensitive Help. In many places in the user interface, you can get

context-sensitive Help.

 Dialog box Help buttons. Most dialog boxes have a Help button that takes you

directly to a Help topic for that dialog box. The Help topic provides general
information and links to related topics.

 Dialog box context menu Help. Many dialog boxes provide context-sensitive Help

for individual controls and features. Right-click on any control in a dialog box and

What’s This? from the context menu to display a description of the control

select
and directions for its use. (If

What’s This? does not appear on the context menu,

then this form of Help is not available for that dialog box.)

 Pivot table context menu Help. Right-click on terms in an activated pivot table in

the Viewer and select

What’s This? from the context menu to display definitions

of the terms.

 Case Studies. Right-clickonapivottableandselectCase Studies from the context

menu to go directly to a detailed example for the procedure that produced that
table. (If

Case Studies does not appear on the context menu, then this form of

Help is not available for that procedure.)

 Command syntax. In a command syntax window, position the cursor anywhere

within a syntax block for a command and press F1 on the keyboard. A complete
command syntax chart for that command will be displayed. Complete command
syntax documentation is available from the links in the list of related topics and
from the Help Contents tab.

 Scripting and OLE automation. In a script window (File menu, New or Open, Script),

the Help menu provides access to information on the scripting language and SPSS
OLE automation objects, methods, and properties. Context-sensitive Help in a
script window is available with F1 or F2 (object browser).

Getting Help

Microsoft Internet Explorer Settings

Most Help features in this application use technology based on Microsoft Internet
Explorer. Some versions of Internet Explorer (including the version provided with
Microsoft XP, Service Pack 2) will by default block what it considers “active content”
in Internet Explorer windows on your local computer. This d efault setting may result
in some blocked content in Help features. To see all Help content, you can change
the default behavior of Internet Explorer.

E From the Internet Explorer menus choose:

To ol s

Internet Options...

E

Click the Advanced tab.

E Scroll down to the Security section.

E Select (check) AllowactivecontenttoruninfilesonMyComputer.

Other Resources

17

If you can’t find the information you want in the Help system, these other resources
may have the answers you need:

 SPSS for Windows Developer’s Guide. Provides information and examples for the

developer’s tools included with SPSS for Windows, including OLE automation,
third-party API, input/output DLL, Production Facility, and Scripting Facility.
The Developer’s Guide is available in PDF form in the SPSS\developer directory
on the installation CD.

 Technical Support Web site. Answerstomanycommonproblems can be found at

http://support.spss.com. (The Technical Support Web site requires a login ID
andpassword. InformationonhowtoobtainanIDandpasswordisprovidedat
the URL listed above.)

Using the Help Table of Contents

E In any window, from the menus choose:

Help

To pi c s

E

Click the Contents tab.

18

Chapter 2

Double-click items with a book icon to expand or collapse the contents.

E

E ClickanitemtogotothatHelptopic.

Figure 2-1

Help window with Contents tab displayed

Using the H

E In any win

Help

To pi c s

E

Click the Index tab.

E Enter a term to search for in the index.

E Double-click the topic that you want.

The Help index uses incremental search to find the text that you enter and selects
the closes

elp Index

dow, from the menus choose:

t match in the index.

Figure 2-2

Index tab and increment al search

Using Help Search

19

Getting Help

The Search tab provides full-text search that includes topic titles, topic text, and
index text. Topics are ranked based on how many times the search term(s) appear in
the topic a

nd/or its index.

20

Chapter 2

Figure 2-3

Help Search tab

 Full-text search is most effective if you can refine your search criteria to limit the

number of topics in the list. For example, if you know you want to find a function
for truncating numeric values, “truncate f unction” will produce a better list of
potential topics than simply “truncate.”

 Topics with a command name in parentheses indicate that the Help topic is for

command syntax. Topics without a command name in parentheses are generally
Help topics for the dialog boxes and other graphical user interface topics.

Getting Help on Dialog Box Controls

E Right-click on the dialog box control that you want information about.

E Choose What’s This? from the pop-up context menu.

A description of the control and how to use it is displayed in a pop-up window. General
information about a dialog box is available from the Help button in the dialog box.

Figure 2-4

Dialog box control Help with right mouse button

Getting Help on Output Terms

E Double-click the pivot table to activate it.

E Right-click on the term that you want to be explained.

21

Getting Help

E Choose What’s This? from the context menu.

A definitio

n of the term is displayed in a pop-up window.

22

Chapter 2

Figure 2-5

Activated pivot table glossary Help with right mouse button

Using Case

E Right-cl

E Choose Ca

Studies

ick on a pivot table in the Viewer window.

se Studies

from the pop-up context menu.

Copying H elp Text from a Pop-Up Window

E Right-click anywhere in the pop-up window.

E Choose Copy from the context menu.

The entir

e text of the pop-up window is copied.

Data Files

Data files come in a wide variety of formats, and this software is designed to handle
many of them, including:

 Spreadsheets created with Excel and Lotus

 Database tables from many database sources, including Oracle, SQLServer,

Access, dBASE, and others

 Tab-delimited and other types of simple text files

 Data files in SPSS format created on other operating systems

 SYSTAT data files

 SAS data files

 Stata data files

Chapter

3

Opening a Data File

In addition to files saved in SPSS format, you can open Excel, SAS, Stata, tab-delimited
and other files without converting the files toanintermediateformatorenteringdata
definition information.

To Open Data Files

E From the menus choose:

File

Open

Data...

E

In the Open File dialog box, select the file that you want to ope

E Click Open.

n.

23

24

Chapter 3

Optionally, you can:

 Read variable names from the first row for spreadsheet and tab-delimited files.

 Specify a range o f cells to read for spreadsheet files.

 Specify a sheet within an Excel file to read (Excel 5 or later).

Data File Types

SPSS. Opens data files saved in SPSS format, including SPSS for Windows, Macintosh,

UNIX, and also the DOS product SPSS/PC+.

SPSS/PC+. Opens SPSS/PC+ data files.

SYSTAT. Opens SYSTAT data files.

SPSS Portable. Opens data files saved in SPSS p

ortable format. Saving a file in portable

format takes considerably longer than saving the file in SPSS format.

Excel. Opens Excel files.

Lotus 1-2-3. Opens data files saved in 1-2-3 format for release 3.0, 2.0, or 1A of Lotus.

SYLK. Opens data files saved in SYLK (symbolic link) format, a format used by some

spreadsheet applications.

dBASE. Opens dBASE-format files for either dBASE IV, dBASE III or III PLUS,

or dBASE II. Each case is a record. Variable and value labels and missing-value
specifications are lost when you save a file in this format.

SAS Long File Name. SAS versions 7–9 for Windows, long extension.

SAS Short File Name. SAS versions 7–9 for Windows, short extension.

SAS v6 for Windows. SAS version 6.08 for Windows and OS2.

SAS v6 for UNIX. SAS version 6 for UNIX (Sun, HP, IBM).

SAS Transport. SAS transport file.

Stata. Stata versions 4–8.

Text. ASCII text file.

Opening File Options

Read variable names. For spreadsheets, you can read variable names from the first row

of the file or the first row of the defined range. The values are converted as necessary
to create valid variable names, including converting spaces to underscores.

Worksheet. Excel 5 or later files c an contain multiple worksheets. By default, the Data

Editor reads the first worksheet. To read a different worksheet, select the worksheet
from the drop-down list.

Range. For spreadsheet data files, you can also read a range of cells. Use the same

method for specifying cell ranges as you would with the spreadsheet application.

Reading Excel 5 or L ater Files

The following rules apply to reading Excel 5 or later files:

Data type and width. Each column is a variable. The data type and width for each

variable are determined by the data type and width in the Excel file. If the column
contains more than one data type (for example, date and numeric), the data type is set
to string, and all values are read as valid string values.

25

Data Files

Blank cells. For numeric variables, blank cells are converted to the system-missing

value, indicated by a period. For string variables, a blank is a valid string value, and
blank cells are treated as valid string values.

Variable names. If you read the first row of the Excel file (or the first row of the

specified range) as variable names, values that don’t conform to variable naming rules
are converted to valid variable names, and the original names are used as variable
labels. If you do not read variable names from the Excel file, default variable names
are assigned.

26

Chapter 3

Reading Older Excel Files and Other Spreadsheets

The following rules apply to reading Excel files prior to version 5 and other spreadsheet
data:

Data type and width. The data type and width for each variable are determined by the

column width and data type of the first data cell in the column. Values of other types
are converted to the system-missing value. If the first data cell in the column is blank,
the global default data type for the spreadsheet (usually numeric) is used.

Blank cells. For numeric variables, blank cells are converted to the system-missing

value, indicated by a period. For string variables, a blank is a valid string value, and
blank cells are treated as valid string values.

Variable names. If you do not read variable names from the spreadsheet, the column

letters (A, B, C, ...) are used for variable names for Excel and Lotus files. For SYLK
files and Excel files saved in R1C1 display format, the software uses the column
number preceded by the letter C for variable names (C1, C2, C3, ...).

Reading dBASE F iles

Database files are logically very similar to SPSS-format data files. The following
general rules apply to dBASE files:

 Field names are converted to valid variable names.

 Colons used in dBASE field names are translated to underscores.

 Records marked for deletion but not actually purged are included. The software

creates a new string variable, D_R, which contains an asterisk for cases marked
for deletion.

Reading Stata Files

The following general rules apply to Stata data files:

 Variable names. Stata variable names are converted to SPSS variable names

in case-sensitive form. Stata variable names that are identical except for case
are converted to valid SPSS variable names by appending an underscore and a
sequential letter (_A, _B, _C,...,_Z, _AA, _AB, ..., etc.).

 Variable labels. Stata variable labels are converted to SPSS variable labels.

Value labels. Stata value labels are converted to SPSS value labels, except for Stata



value labels assigned to “extended” missing values.

 Missing values. Stata “extended” missing values are converted to system-missing.

 Data conversion. Stata date format values are converted to SPSS DATE format

(d-m-y) values. Stata “time-series” date format values (weeks, months, quarters,
etc.) are converted to simple numeric (F) format, preserving the original, internal
integer value which is the number of weeks, months, quarters, etc., since the start
of 1960.

Reading Database Files

You can read data from any database format for which you have a database driver. In
local analysis mode, the necessary drivers must be installed on your local computer. In
distributed analysis mode (available with SPSS Server), the drivers must be installed
on the remote server. For more information, see “Distributed Analysis Mode” in
Chapter 4 on p. 73.

27

Data Files

To Read Database Files

E From the menus choose:

File

Open Database

New Query...

E

Selectthedatasource.

E If necessary (depending on the data source), select the database file and/or enter a login

name, password, and other information.

E Select the table(s) and fields. (For OLE DB data sources, you can only select one table.)

E Specify any relationships between your tables.

E Optionally:

 Specify any selection criteria for your data.

 Add a prompt for user input to create a parameter query.

 Save your constructed query before running it.

28

Chapter 3

To Edit Saved Database Queries

E From the menus choose:

File

Open Database

Edit Query...

E

Select the query file (*.spq) that you want to edit.

E Follow the instructions for cre

ating a new query.

To Read Database Files with Saved Queries

E From the menus choose:

File

Open Database

Run Query...

E

Select the query file (*.spq) that you want to r

E If necessary (depending on the database file), enter a login name and password.

E If the query has an embedded prompt, enter other inform

example, the quarter for which you want to retrieve sales figures).

Selecting a Data Source

Use the first screen of the Database Wizard to select the type of data source to read.

un.

ation if necessary (for

ODBC Data Sources

If you do not have any ODBC data sources configured, or if you want to add a new
data source, click AddODBCDataSource. In distributed analysis mode (a

vailable with
SPSS Server), this button is not available. To add data sources in distributed analysis
mode, see your system administrator.

Data Files

An ODBC data source consists of two essential pieces of information: the driver
that will be used to access the data and the location of the database that you want to
access. To specify data sources, you must have the appropriate drivers installed. For
local analysis mode, you can install drivers from the CD-ROM for this product:

 SPSS Data Access Pack. Installs drivers for a variety of database formats. This

feature is available on the AutoPlay menu.

 Microsoft Data Access Pack. Installs drivers for Microsoft products, including

Microsoft Access. To install the Microsoft Data Access Pack, double-click

Microsoft Data Access Pack in the Microsoft Data Access Pack folder on the

CD-ROM.

Figure 3-1

Database Wizard dialog box

29

30

Chapter 3

OLE DB Data Sources

To access OLE DB data sources, you must have the following items installed on the
computer that is running SPSS:

 .NET framework

 Dimensions Data Model and OLE DB Access

Versions of these components that are compatible with this release of SPSS can be
installed from the SPSS installation CD and are available on the AutoPlay menu.

 You can only add OLE DB data sources in local analysis mode. To add OLE

DB data sources in distributed analysis mode on a Windows server, consult your
system administrator.

 In distributed analysis mode (available with SPSS Server), OLE DB data sources

are only available on Windows servers, and both .NET and the Dimensions Data
Model and OLE DB Access must be installed on the server.

Figure 3-2

Database Wizard with access to OLE DB data sources

31

Data Files

To add an OLE DB data source:

E Click Add OLE DB Data Source.

E In the Data Link Properties dialog box, click the Provider tab and select the OLE DB

provider.

E Click Next or click the Connection tab.

E Select the database by entering the directory location and database name or by clicking

the button to browse to a database. (A user name and password may also be required.)

E Click OK after entering all necessary information. (You can make sure the specified

database is available by clicking the

E Enter a name for the database connection information. (This name will be displayed in

Test Connection button.)

the list of available OLE DB data sources.)

32

Chapter 3

Figure 3-3

Save OLE DB Connection Information As dialog box

E Click OK.

This takes you back to the first screen of the Database Wizard, where you can select
the saved name from the list of OLE DB data sources and continue to the next step
of the wizard.

Database Login

If your ODBC database requires a password, the Database Wizard will prompt you for
password before it can open the data source.

Figure 3-4

Logindialogbox

Selecting Data Fields

The Select Data dialog box controls which tables and fields are read. Database fields
(columns) are read as variables.

Data Files

If a table has any field(s) selected, all of its fields will be visible in the following
Database Wizard windows, but only fields that are selected in this dialog box will b e
imported as variables. This enables you to create table joins and to specify criteria by
using fields that you are not importing.

Figure 3-5

Select Data dialog box

33

Displaying field names. To list the fields in a table, click the plus sign (+) to the left of a

table name. To hide the fields, click the minus sign (–) to the left of a table name.

To add a field. Double-click any field in the Available Tables list, or drag it to the

Retrieve Fields In This Order list. Fields can be reordered by dragging and dropping
them within the fields list.

To remove a field. Double-click any field in the Retrieve Fields In This Order list, or

drag it to the Available Tables list.

Sort field names. If this check box is selected, the Database Wizard will display your

available fields in a lphabetical order.

34

Chapter 3

Note: For OLE DB data sources, you can select fields only from a single table.
Multiple table joins are not supported for OLE DB data sources.

Creating a Relationship between Tables

The Specify Relationships dialog box allows you to define the relationships between
the tables for ODBC data sources. If fields from more than one table are selected,
you must define at least one join.

Figure 3-6

Specify Relationships dialog box

Establishing relationships. To create a relationship, drag a field from any table onto the

field to which you want to join it. The Database Wizard will draw a join line between
the two fields, indicating their relationship. These fields must be of the same data type.

Auto Join Tables. Attempts to automatically join tables based on primary/foreign keys

or matching field names and data type.

Specifying join types. If outer joins are supported by your driver, you can specify inner

joins, left outer joins, or right outer joins. To select the type of join, double-click the
join line between the fields, and the wizard will display the Relationship Properties
dialog box.

Relationship Properties

This dialog box allows you to specify which type of relationship joins your tables.

Figure 3-7

Relationship Properties dialog box

35

Data Files

Inner joins. An inner join includes only rows where the related fields are equal. In this

example, all rows with matching ID values in the two tables will be included.

Outer joins. In addition to one-to-one matching with inn er joins, you can also use

outer joins to merge tables with a one-to-many matching scheme. For example, you
could match a table in which there are only a few records representing data values and
associated descriptive labels with values in a table containing hundreds or thousands of
records representing survey respondents. A left outer join includes all records from the
table on the left and, from the table on the right, includes only those records in which
the related fields are equal. In a right outer join, the join imports all records from the
table on the right and, from the table on the left, imports only those records in which
the related fields are equal.

36

Chapter 3

Limiting Retrieved Cases

The Limit Retrieved Cases dialog box allows you to specify the criteria to select
subsets of cases (rows). Limiting cases generally consists of filling the criteria grid
with criteria. Criteria consist of two expressions and some relation between them. The
expressions return a value of true, false,ormissing for each case.

 If the result is true, t he case is selected.

 If the result is false or missing, the case is not selected.

 Most criteria use one or more of the six relational operators (<, >, <=, >=, =, and

<>).

 Expressions can include field names, constants, arithmetic operators, numeric and

other functions, and logical variables. You can use fields that you do not plan
to import as variables.

Figure 3-8

Limit Retrieved Cases dialog box

Data Files

To build your criteria, you need at least two expressions and a relation to connect
the expressions.

37

E To bui l

d an expression, choose one of the following methods:

 In an Ex

pression cell, type field names, constants, arithmetic operators, numeric

and other functions, or logical variables.

 Double-click the field in the Fields list.

 Drag the field from the Fields list to an Expression cell.

 Choose a field from the drop-down menu in any active Expression cell.

E To choose the relational operator (such as = or >), put your cursor in the Relation cell

and either type the operator or choose it from the drop-down menu.

Dates and times in expressions need to be specified in a special manner (including the
curly braces that are shown in the examples):

 Date literals should be specified by using the general form: {d yyyy-mm-dd}.

 Time literals should be specified by using the general form: {t hh:mm:ss}.

 Date/time literals (timestamps) should be specified by using the general form: {dt

yyyy-mm-dd hh:mm:ss}.

Functions. A selection of built-in arithmetic, logical, string, date, and time SQL

functions is provided. You can drag a function from the list into the expression, or you
can enter any valid SQL function. See your database documentation for valid SQL
functions. A list of standard functions is available at:

http://msdn.microsoft.com/library/en-us/odbc/htm/odbcscalar_functions.asp

Use R andom Sampling. This option selects a random sample of cases from the data

source. For large data sources, you may want to l imit the number of cases to a small,
representative sample, which can significantly reduce the time that it takes to run
procedures. Native random sampling, if available for the data source, is faster than
SPSS random sampling, because SPSS random sampling must still read the entire
data source to extract a random sample.

 Approximately. Generates a random sample of approximately the specified

percentage of cases. Since this routine makes an independent pseudo-random
decision for each case, the percentage of cases selected can only approximate

38

Chapter 3

the specified percentage. The more cases there are in the data file, the closer the
percentage of cases selected is to the specified percentage.

 Exactly. Selects a random sample of the specified number of cases from the

specified total number of cases. If the total number of cases specified exceeds
the total number of cases in the data file, the sample will contain p roportionally
fewer cases than the requested number.

Note: If you use random sampling, aggregation (available in distributed mode with
SPSS Server) is not available.

Prompt For Value. You can embed a prompt in your query to create a parameter query.

Whenusersrunthequery,theywillbeaskedtoenterinformation(basedonwhatis
specified here). You might want to do this if you need to see different views of the
same data. For example, you may want to run the same query to see sales figures for
different fiscal quarters.

E Place your cursor in any Expression cell, and click Prompt For Value to create a prompt.

Creating a Parameter Query

Use the Prompt for Value dialog box to create a dialog box that solicits information
from users each time someone runs your query. This feature is useful if you want to
query the same data source by using different criteria.

Figure 3-9

Prompt for Value dialog box

Data Files

To build a prompt, enter a prompt string and a default value. The prompt string is
displayed each time a user runs your query. The string should specify the kind of
information to enter. If the user is not selecting from a list, the string should give
hints about how the input should be formatted. An example is as follows:

Quarter (Q1, Q2, Q3, ...)

Allow u ser to select value from list. If this check box is selected, you can limit the u ser

.

Enter a

to the values that you place here. Ensure that your values are separated by returns.

Data type. Choosethedatatypehere(Number, String,orDate).

The final result looks like this:

Figure 3-10

User-defined prompt dialog box

39

Aggregating Data

If you are in distributed mode, connected to a remote server (available with SPSS
Server), you can aggregate the data before reading it into SPSS.

40

Chapter 3

Figure 3-11

Aggregate Data dialog box

You can also aggregate data after reading it into SPSS, but preaggregating may save
timeforlargedatasources.

E To create aggregated data, select one or more break variables that define how cases

are g rou

E Select

E Select

E Option

ped.

one or more aggregated variables.

an aggregate function for each aggregate variable.

ally, create a variable that contains the number of cases in each break group.

Note: If you use random sampling, aggregation is not available.

Defining Variables

Variable names and labels. The complete database field (column) name is used as the

variable label. Unless you modify the variable name, the Database Wizard assigns
variable names to each column from the database in one of two ways:

 If the name of the database field forms a valid, unique variable name, the name

is used as the variable name.

 If the name of the database field does not form a valid, unique variable name, a

new, unique name is automatically generated.

Click any cell to edit the variable name.

Converting strings to numeric values. Select the Recode to Numeric box for a string

variable if you want to automatically convert it to a numeric variable. String values
are converted to consecutive integer values based on alphabetical order of the original
values. The original values are retained as value labels for the new variables.

Width for variable-width string fields. For ODBC data sources, this option controls the

width of variable-width string values. By default, the width is 255 bytes, and only the
first 255 bytes (typically 255 characters in single-byte languages) will be read. The
width can be up to 32,767 bytes. Although you probably don’t want to truncate string
values, you also don’t want to specify an unnecessarily large value, which will cause
SPSS processing to be inefficient.

41

Data Files

Note: For OLE DB data sources, variable-width strings are set to the maximum width:
32,767 bytes. If any string values in a record exceed that width, the record is excluded.

42

Chapter 3

Figure 3-12

Define Variables dialog box

Sorting

Cases

If you ar
Server), you can sort the data before reading it into SPSS.

e in distributed mode, connected to a remote server (available with SPSS

Figure 3-13

Sort Case s dialog box

43

Data Files

Results

You can also sort data after reading it into SPSS, but presorting may save time for
largedatasources.

The Results dialog box displays the SQL Select statement for your query.

 You can edit the SQL Select statement before you run the query, but if you click

Back button to make changes in previous steps, the changes to the Select

the
statement will be lost.

 To save the query for future use, use the Save query to file section.

 To paste complete GET DATA syntax into a syntax window, select Pasteitintothe

syntax editor for further modification

. Copying and pasting the S elect statement from

the Results window will not paste the necessary command syntax.

44

Chapter 3

Note: The pasted syntax contains a blank space before the closing quote on each line
of SQL that is generated by the wizard. These blanks are not superfluous. When the
command is processed, all lines of the SQL statement are merged together in a very
literal fashion. Without the space, there would be no space between the last character
on one line and first character on the next line.

Figure 3-14

Results dialog box

Text Wizard

The Text Wizard can read text data files formatted in a variety of ways:

 Tab-delimited files

 Space-delimited files

 Comma-delimited files

 Fixed-field format files

For delimited files, you can also specify other characters as delimiters between values,
and you can specify multiple delimiters.

To Read Text Data Files

E From the menus choose:

File

Read Text Data...

E

Select the text file in the Open File dialog box.

E Follow the steps in the Text Wizard to define how to read the data file.

Text Wizard: Step 1

Figure 3-15

Text Wizard: Step 1

45

Data Files

46

Chapter 3

The text file is displayed in a preview window. You can apply a predefined format
(previously saved from the Text Wizard) or follow the steps in the Text Wizard to
specifyhowthedatashouldberead.

Text Wizard: Step 2

Figure 3-16

Text Wizard: Step 2

This step provides information about variables. A variable is similar to a field in a
database. For example, each item in a questionnaire is a variable.

How are

your variables arranged?

To read your data properly, the Text Wizard needs to
know how to determine where the data value for one variable ends and the data value
for the next variable begins. The arrangement of variables defines the method used to

rentiate one variable from the next.

diffe

Delimited. Spaces, commas, tabs, or other characters are used to separate variables.



The variables are recorded in the same order for each case but not necessarily
in the same column locations.

 Fixed width. Each variable is recorded in the same column location on the same

record (line) for each case in the data file. No delimiter is required between
variables. In fact, in many text data files generated by computer programs, data
values may appear to run together without even spaces separating them. The
column location determines which variable is being read.

Are variable names included at the top of your file? If the first row of the data file contains

descriptive labels for each variable, you can use these labels as variable names. Values
that don’t conform to variable naming rules are converted to valid variable names.

Text Wizard: Step 3 (Delimited Files)

Figure 3-17

Text Wizard: Step 3 (for delimite d files)

47

Data Files

48

Chapter 3

This step provides information about cases. A case is similar to a record in a database.
For example, each respondent to a questionnaire is a case.

The first case of data begins on which line number? Indicates the first line of the data file

that contains data values. If the top line(s) of the data file contain descriptive labels or
other text that does not represent data values, this will not be line 1.

How are your cases represented? Controls how the Text Wizard determines where

each case ends and the next one begins.

 Each line represents a case. Each line contains only one case. It is fairly common

for each case to be contained on a single line (row), even though this can be a very
long line for data files with a large number of variables. If not all lines contain the
same number of data values, the number of variables for each case is determined
by the line with the greatest number of data values. Cases with fewer data values
are assigned missing values for the additional variables.

 A specific number of variables represents a case. The specified number of variables

for each case tells the Text Wizard where to stop reading one case and start reading
the next. Multiple cases can be contained on the same line, and cases can start
in the middle of one line and be continued on the next line. The Text Wizard
determines the end of each case based on the number of values read, regardless
of the number of lines. Each case must contain data values (or missing values
indicated by delimiters) for all variables, or the data file will be read incorrectly.

How m any cases do you want to import? You can import all cases in the data file, the

first n cases (n is a number you specify), or a random sample of a specified percentage.
Since the random sampling routine makes an independent pseudo-random decision
for each case, the percentage of cases selected can only approximate the specified
percentage. The more cases there are in the data file, the closer the percentage of cases
selected is to the specified percentage.

49

Data Files

Text Wizard: Ste

Figure 3-18

TextWizard: Step3(forfixed-widthfiles)

p 3 (Fixed-Width Files)

This step provides information about cases. A case is similar to a record in a database.
For example, each respondent to questionnaire is a case.

The first case of data begins on which line number? Indicates the first line of the data file

that contains data values. If the top line(s) of the data file contain descriptive labels or
other text that does not represent data values, this will not be line 1.

How many lines represent a case? Controls how the Text Wizard determines where

each case ends and the next one begins. Each variable is defined by its line number
within the case and its column location. You need to specify the number of lines
for each case to read the data correctly.

How m any cases do you want to import? You can import all cases in the data file, the

first n cases (n is a number you specify), or a random sample of a specified percentage.
Since the random sampling routine makes an independent pseudo-random decision
for each case, the percentage of cases selected can only approximate the specified

50

Chapter 3

percentage. The more cases there are in the data file, the closer the percentage of cases
selected is to the specified percentage.

Text Wizard: Step 4 (Delimited Files)

Figure 3-19

Text Wizard: Step 4 (for delimite d files)

This step displays the Text Wizard’s best guess on how to read the data file and allows
you to modify how the Text Wizard will read variables from the data file.

Which delimiters appear between variables? Indicates the characters or symbols that

separate data values. You can select any combination of spaces, commas, semicolons,
tabs, or other characters. Multiple, consecutive delimiters without intervening data
values are t reated as missing values.

What is the text qualifier? Characters used to enclose values that contain delimiter

characters. For example, if a comma is the delimiter, values that contain commas will
be read incorrectly unless there is a text qualifier enclosing the value, preventing the

commas in the value from being interpreted as delimiters between values. CSV-format
data files exported from Excel use a double quotation mark (“) as a text qualifier.
The text qualifier appears at both the beginning and the end of the value, enclosing
the entire value.

Text Wizard: Step 4 (Fixed-Width Files)

Figure 3-20

TextWizard: Step4(forfixed-widthfiles)

51

Data Files

This step displays the Text Wizard’s best guess on how to read the data file and allows
you to modify how the Text Wizard will read variables from the data file. Vertical lines
in the preview window indicate where the Text Wizard currently thinks each variable
begins in the file.

Insert, move, and delete variable break lines as necessary to separate variables. If
multiple lines are used for each case, select each line from the drop-down list and
modify the variable break lines as necessary.

52

Chapter 3

Notes:

For computer-generated data files that produce a continuous stream of data values with
no intervening spaces or other distinguishing characteristics, it may be difficult to
determine where each variable begins. Such data files usually rely on a data definition
file or some other written description that specifies the line and column location for
each variable.

The Text Wizard is designed for use with a monospaced (fixed-pitch) font to display
the file contents. With non-monospaced (proportional) fonts, the file content will not
align properly. This font setting is controlled by the Text Output Font setting on the
Viewer tab of the Options dialog box (Edit menu).

Text Wizard: Step 5

Figure 3-21

Text Wizard: Step 5

This steps controls the variable name and the data format that the Text Wizard will use
to read each variable and which variables will be included in the final data file.

Variable name. You can overwrite the default variable names with your own

variable names. If you read variable names from the data file, the Text Wizard will
automatically modify variable names that don’t conform to variable naming rules.
Select a variable in the preview window and then enter a variable name.

Data for mat. Select a variable in the preview window and then select a format from the

drop-down list. Shift-click to select multiple contiguous variables or Ctrl-click to
select multiple noncontiguous variables.

Text Wizard Formatting Options

Formatting options for reading variables with the Text Wizard include:

Do not import. Omit the selected variable(s) from the imported data file.

Numeric. Valid values include numbers, a leading plus or minus sign, and a decimal

indicator.

53

Data Files

String. Valid values include virtually any k

eyboard characters and embedded blanks.
For delimited files, you can specify the number of characters in the value, up to a
maximum of 32,767. By default, the Text Wizard sets the number of characters to the
longest string value encountered for the s

elected variable(s). For fixed-width files, the
number of characters in string values is defined by the placement of variable break
lines in step 4.

Date/Time. Valid values include dates of the general format dd-mm-yyyy, mm/dd/yyyy,

dd.mm.yyyy, yyyy/mm/dd, hh:mm:ss, and a variety of other date and time formats.

Months can be represented in digits, Roman numerals, or thr ee-letter abbreviations, or
they can be fully spelled out. Select a date format from the list.

Dollar. Validvaluesarenumberswithanoptional leading dollar sign and optional

commas as thousands separators.

Comma. Valid values include numbers that use a period as a decimal indicator and

commas as thousands separators.

Dot. Valid values include numbers that use a comma as a decimal indicator and periods

as thousands separators.

54

Chapter 3

Note: Values that contain invalid characters for the selected format will be treated as
missing. Values that contain any of the specified delimiters will be treated as multiple
values.

Text Wizard: Step 6

Figure 3-22

Text Wizard: Step 6

This is the final step of the Text Wizard. You can save your specifications in a file for
use when importing similar text data files. You can also paste the syntax generated by
the Tex

t Wizard into a syntax window. You can then customize and/or save the syntax

for use in other sessions or in production jobs.

Cache data locally. A data cache is a complete copy of the data file, stored in temporary

disk space. Caching the data file can improve performance.

Reading Dimensions Data

You can read data from SPSS Dimensions products, including Quanvert, Quancept,
and mrInterview.

To read Dimensions data sources, you must have the following items installed on the
computer that is running SPSS:

 .NET framework

 Dimensions Data Model and OLE DB Access

Versions of these components that are compatible with this release of SPSS can be
installed from the SPSS installation CD and are available on the AutoPlay menu. You
can only read Dimensions data sources in local analysis mode. This feature is not
available in distributed analysis mode using SPSS Server.

To read data from a Dimensions data source:

E In any open SPSS window, from the menus choose:

File

Open Dimensions Data

55

Data Files

E

On the Connection tab of Data Link Properties, specify the metadata file, the case
data type, and the case data file.

E Click OK.

E In the Dimensions Data Import dialog box, select the variables that you want to include

and select any case selection criteria.

E Click OK to read the data.

Data Link Properties Connection Tab

To read a Dimensions data source, you need to specify:

Metadata Location. The metadata document file (.mdd) that contains questionnaire

definition information.

Case Data Type. The format of the case data file. Available formats include:

 Quancept Data File (DRS). Case data in a Quancept .drs, .drz,or.dru file.

56

Chapter 3

Quanvert Database. Case data in a Quanvert database.



 Dimensions Database (MS SQL Server). Case data in an SPSS MR relational

database in SQL Server. This option can be used to read data that are collected
by using mrInterview.

 Dimensions XML Data File. Case data in an XML file.

Case Data Location. The file that contains the case data. The format o f this file must be

consistent with the selected case data type.

Figure 3-23

Data Li nk Properties: Connection tab

Note: The extent to which other settings on the Connection tab or any settings on the
other Data Link Properties tabs may or may not affect reading Dimensions data into
SPSS is not known, so we recommend that you do not change any of them.

Select Variables Tab

You can select a subset of variables to read. By d efault, all standard variables in the
data source are displayed and selected.

 Show System variables. Displays any “system” variables, including variables

that indicate interview status (in progress, completed, finish date,etc.).Youcan
then select any system variables that you want to include. By default, all system
variables are excluded.

 Show Codes variables. Displays any variables that represent codes that are used

for open-ended “Other” responses for categorical variables. You can then select
any Codes variables that you want to include. By default, all Codes variables
are excluded.

 Show SourceFile variables. Displays any variables that contain filenames of images

of scanned responses. You can then select any SourceFile variables that you want
to include. By default, all SourceFile variables are excluded.

Figure 3-24

Dimensions Data Import: Select Variables tab

57

Data Files

58

Chapter 3

Case Selection Tab

For Dimensions data sources that contain system variables, you can select cases based
on a number of system variable criteria. You do not need to include the corresponding
system variables in the list of variables to read, but the necessary system variables must
exist in the source data to apply the selection criteria. If the necessary system variables
do not exist in the source data, the corresponding selection criteria are ignored.

Data collection status. You can select respondent data, test data, or both. You can also

select cases based on any combination of the following interview status parameters:

 Completed successfully

 Active/in progress

 Timed out

 Stopped by script

 Stopped by respondent

 Interview system shutdown

 Signal (terminated by a signal statement in the script)

Data collection finish date. You can select cases based on the data collection finish date.

 Start Date. Cases for which data collection finished on or after the specified date

are included.

 End Date. Cases for which data collection finished before the specified date are

included. This does not include cases for which data collection finished on the
end date.

 If you specify both a start date and end date, this defines a range of finish dates

from the start date to (but not including) the end date.

Figure 3-25

Dimensions Data Import: Case Selection tab

59

Data Files

File Inf

ormation

Adatafi
information, including:

 Va ri ab l e na me s

 Variable formats

 Descriptive variable and value labels

This information is stored in the dictionary portion of the data file. The Data Editor
provide
complete dictionary information for the active dataset or any other data file.

le contains much more than raw data. It also contains any variable definition

s one way to view the variable definition information. You can also display

60

Chapter 3

To Obtain Data File Information

E From the menus in the Data Editor window choose:

File

Display Data File Information

E

For the currently open data file, choose Working File.

E For other data files, choose External File, and then select the data file.

The data file information is displayed in the Viewer.

Saving Data Files

Any changes that you make in a data file last only for the duration of the current
session—unless you explicitly save the changes.

To Save Modified Data Files

E Make the Data Editor the active window (click anywhere in the window to make

it active).

E From the menus choose:

File

Save

Themodifieddatafileissaved,overwritingthepreviousversionofthefile.

Saving Data Files in Excel Format

You can save your data in one of three Microsoft Excel file formats. The choice of
format depends on the version of Excel that will be used to open the data. The Excel
application cannot open an Excel file from a newer version of the application. For
example, Excel 5.0 cannot open an Excel 2000 document. However, Excel 2000 can
easilyreadanExcel5.0document.

ThereareafewlimitationstotheExcelfile format that don’t exist in SPSS. These

limitations include:

 Variable information, such as missing values and variable labels, is not included

in exported Excel files.

Data Files

When exporting to Excel 97 and later, an option is provided to include value labels



instead of values.

 Because all Excel files are limited to 256 columns of data, only the first 256

variables are included in the exported file.

 Excel 4.0 and Excel 5.0/95 files are limited to 16,384 records, or rows of data.

Excel 97–2000 files allow 65,536 records. If your data exceed these limits, a
warning message is displayed and the data are truncated to the maximum size
allowed by Excel.

Variable Types

The following table shows the variable type matching between the original data in
SPSS and the exported data in Excel.

SPSS Variable Type Excel Data Format

Numeric 0.00; #,##0.00; ...

Comma 0.00; #,##0.00; ...

Dollar

Date d-mmm-yyyy

Time hh:mm:ss

String General

$#,##0_); ...

61

Saving Data Files in SAS Format

Special handling is given to various aspects of your data when saved as a SAS file.
These cases include:

 CertaincharactersthatareallowedinSPSSvariablenamesarenotvalidinSAS,

such as @, #, and $. These illegal characters are replaced with an underscore when
the data are exported.

 SPSS variable names that contain multi-byte characters (for example, Japanese or

Chinese characters) are converted to variables names of the general form Vnnn,
where nnn is an integer value.

 SPSS variable labels containing more than 40 characters are truncated when

exported to a SAS v6 file.

62

Chapter 3

Where they exist, SPSS variable labels are mapped to the SAS variable labels.



If no variable label exists in the SPSS data, the variable name is mapped to the
SAS variable label.

 SAS allows only one value for system-missing, whereas SPSS allows numerous

system-missing values. As a result, all system-missing values in SPSS are mapped
to a single system-missing value in the SAS file.

Save Value Labels

You have the option of saving the values and value labels associated with your data file
to a SAS syntax file. For example, when the value labels for the cars.sav data file are
exported, the generated syntax file contains:

libname library 'd:\spss\' ;

proc format library = library ;

value ORIGIN /* Country of Origin */

1 = 'American'

2 = 'European'

3 = 'Japanese' ;

value CYLINDER /* Number of Cylinders */

3 = '3 Cylinders'

4 = '4 Cylinders'

5 = '5 Cylinders'

6 = '6 Cylinders'

8 = '8 Cylinders' ;

value FILTER__ /* cylrec=1|cylrec = 2 (FILTER) */

0 = 'Not Selected'

1 = 'Selected' ;

proc datasets library = library ;

modify cars;

format ORIGIN ORIGIN.;

format CYLINDER CYLINDER.;

Data Files

format FILTER__ FILTER__.;

quit;

This feature is not supported for the SAS transport file.

Variable Types

The following table shows the variable type matching between the original data in
SPSS and the exported data in SAS.

SPSS Variable Type SAS Variable Type SAS Data Format

Numeric Numeric 12

Comma Numeric 12

Dot Numeric 12

Scientific Notation Numeric 12

Date Numeric (Date) for example,

MMDDYY10, ...

Date (Time) Numeric Time18

Dollar Numeric 12

Custom Currency Numeric 12

String Character

$8

63

Saving Data Files in Stata Format

 Data can be written in Stata 5–8 format and in both Intercooled and SE format

(versions 7–8 only).

 Data files that are saved in Stata 5 format can be read by Stata 4.

 The first 80 bytes of variable labels are saved as Stata variable labels.

 For numeric variables, the first 80 bytes of value labels are saved as Stata value

labels. For string variables, value labels are dropped.

 For versions 7 and 8, the first 32 bytes of variable names in case-sensitive form are

saved as Stata variable names. For earlier versions, the first 8 bytes of variable
names are saved as Stata variable names. Any characters other than letters,
numbers, and underscores are converted to underscores.

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Chapter 3

SPSS variable names that contain multi-byte characters (for example, Japanese or



Chinese characters) are converted to variables names of the general form Vnnn,
where nnn is an integer value.

 For versions 5–6 and Intercooled versions 7–8, the first 80 bytes of string values

are saved. For Stata SE 7 –8, the first 244 bytes o f string values are saved.

 For versions 5–6 and Intercooled versions 7–8, only the first 2,047 variables are

saved. For Stata SE 7–8, only the first 32,767 variables are saved.

SPSS Variable Type Stata Variable Type Stata Data Format

Numeric Numeric

Comma Numeric

Dot Numeric

Scientific Notation Numeric

Date, Datetime Numeric D_m_Y

Time, DTime Numeric g (number of seconds)

Wkday Numeric g (1-7)

Moyr Numeric g (1-12)

Dollar Numeric

Custom Currency Numeric

String String

g

g

g

g

g

g

s

Saving Data Files in Other Formats

E Make the Data Editor the active window (click anywhere in the window to make

it active).

E From the menus choose:

File

Save As...

E

Select a file type from the drop-down list.

E Enter a filename for the new data file.

To write variable names to th e first row of a spreadsheet or tab-delimited data file:

E Click Write variable names to spreadsheet in the Save Data As dialog box.

To save valu e labels instead of data values in Excel 97 format:

E Click Save value labels where defined instead of data values in the Save Data As dialog

box.

To save value labels to a SAS syntax file (active only when a SAS fi le type is selected):

E Click Save value labels into a .sas file intheSaveDataAsdialogbox.

Saving Data: Data File Types

You can save data in the following formats:

SPSS (*.sav). SPSS format.

 Data files saved in SPSS format cannot be read by versions of the software prior

to version 7.5.

 When using data files with variable names longer than eight bytes in SPSS 10.x

or 11.x, unique, eight-byte versions of variable names are used—but the original
variable names are preserved for use in release 12.0 or later. In releases prior to
SPSS 10.0, the original long variable names are lost if you save the data file.

 When using data files with string variables longer than 255 bytes in versions of

SPSS prio r to release 13.0, those string variables are broken up into multiple
255-byte string variables.

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Data Files

SPSS 7.0 (*.sav). SPSS 7.0 for Windows format. Data files saved in SPSS 7.0 format

can be read by SPSS 7.0 and earlier versions of SPSS for Windows but do not include
defined m ultiple response sets or Data Entry for Windows information.

SPSS/PC+ (*.sys). SPSS/PC+ format. If the data file contains more than 500 variables,

only the first 500 will be saved. For variables with more than one defined user-missing
value, additional user-missing values will be recoded into the first defined user-missing
value.

SPSS Portable (*.por). SPSS portable format that can be read by other versions of SPSS

and versions on other operating systems (for examp

le, Macintosh or UNIX). Variable
names are limited to eight bytes and are automatically converted to unique eight-byte
names if necessary.

Tab-delimited (*.dat). ASCII text files with values separated by tabs.

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Chapter 3

Fixed A SCI I (*.dat). ASCII text file in fixed format, using the default write formats for

all variables. There are no tabs or spaces between variable fields.

Excel 2.1 (*.xls). Microsoft Excel 2.1 spreadsheet file. The maximum number of

variables is 256, and the maximum number of rows is 16,384.

Excel 97 and later (*.xls). Microsoft Excel 97/2000/XP spreadsheet file. The maximum

number of variables is 256, and the maximum number of rows is 65,536.

1-2-3 Release 3.0 (*.wk3). Lotus 1-2-3 spreadsheet file, release 3.0. The maximum

number of variables that you can save is 256.

1-2-3 Release 2.0 (*.wk1). Lotus 1-2-3 spreadsheet file, release 2.0. The maximum

number of variables that you can save is 256.

1-2-3 Release 1.0 (*.wks). Lotus 1-2-3 spreadsheet file, release 1A. The maximum

number of variables that you can save is 256.

SYLK (*.slk). Symbolic link

format for Microsoft Excel and Multiplan spreadsheet files.

The maximum number of variables that you can save is 256.

dBASE IV (*.dbf). dBASE IV format.

dBASE III (*.dbf). dBASE III format.

dBASE II (*.dbf). dBASE II format.

SAS v6 for Windows (*.sd2). SAS v6 file format for Windows/OS2.

SAS v6 for UNIX (*.ssd01). SAS v6 file format for UNIX (Sun, HP, IBM).

SAS v6 for Alpha/OSF (*.ssd04). SAS v6 file format for Alpha/OSF (DEC UNIX).

SAS v7+ Windows short extension (*.sd7). SAS versions 7–8 for Windows short filename

format.

SAS v7+ Window s long extension (*.sas7bdat). SAS versions 7–8 for Windows long

filename format.

SAS v7+ for U NIX (*.ssd01). SAS v8 for UNIX.

SAS Transport (*.xpt). SAS transport file.

Stata Versions 4–5 (*.dta).

Stata Version 6 (*.dta).

Stata Version 7 Intercooled (*.dta).

Stata Version 7 SE (*.dta).

Stata Version 8 Intercooled (*.dta).

Stata Version 8 SE (*.dta).

Saving Subsets of Variables

Figure 3-26

Save Data As Variables dialog box

67

Data Files

The Save Data As Variables dialog box allows you to select the variables that you want
to be saved in the new data file. By default, all variables will be saved. Deselect the
variables that you don’t want to save, or click
youwanttosave.

To Save a Subset of Variables

E Make the Data Editor the active window (click anywhere in the window to make

it active).

E From the menus choose:

File

Save As...

E

Select the file types the file type.

E Click Va riabl e s .

Drop All andthenselectthevariablesthat

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Chapter 3

Select the variables that you want to save.

E

Saving File Options

For spreadsheet and tab-delimited files, you can write variable names to the first row
of the file.

Protecting Original Data

To prevent the accidental modification/deletion of your original data, you can mark
the file as read-only.

E From the Data Editor menus choose:

File

Mark File Read Only

If you make subsequent modifications to the data and then try to save the data file, you
can save the data only with a different filename, so the original data are not affected.

You can change the file permissions back to read/write by selecting

Write

from the File menu.

Mark File Read

Virtual Active File

The virtual active file enables you to work with large data files without requiring
equally large (or larger) amounts of temporary disk space. For most analysis and
charting procedures, the original data source is reread each time you run a different
procedure. Procedures that modify the data require a certain amount of temporary disk
space to keep track of the changes, and some actions always require enough disk space
for at least one entire copy of the data file.

Figure 3-27

Temporary disk space requirements

Action

Virtual
Active

File

GET FILE = 'v1-5.sav'. REG RESSION… or

FREQUENCIES… /SAVE ZPRED.

v1 v2 v3 v4 v5 v1 v2 v3 v4 v5 v6 zpre v1 v2 v3 v4 v5 v6 zpre

11 12 13 14 15 11 12 13 14 15 16 1 11 12 13 14 15 16 1

21 22 23 24 25 21 22 23 24 25 26 2 21 22 23 24 25 26 2

31 32 33 34 35 31 32 33 34 35 36 3 31 32 33 34 35 36 3

41 42 43 44 45 41 42 43 44 45 46 4 41 42 43 44 45 46 4

51 52 53 54 55 51 52 53 54 55 56 5 51 52 53 54 55 56 5

61 62 63 64 65 61 62 63 64 65 66 6 61 62 63 64 65 66 6

COMPUTE v6 = …
RECODE v4…

69

Data Files

SORT CASES BY…

CACHE

Data

Stored

in

Tem por a ry

Disk

Space

None

v4 v6 zpre v1 v2 v3 v4 v5 v6 zpre

1416 1 111213141516 1

2426 2 212223242526 2

3436 3 313233343536 3

4446 4 414243444546 4

5456 5 515253545556 5
6466 6 616263646566 6

Actions that don’t require any t emporary disk space include:

 Reading SPSS data files

 Merging two or more SPSS data files

 Reading database tables with the Database Wizard

 Merging an SPSS data file with a database table

 Running procedures that read data (for example, Frequencies, Crosstabs, Explore)

Actions that create one or more column s of data in temporary disk space include:

 Computing new variables

 Recoding existing variables

 Running procedures that create or modify variables (for example, saving predicted

values in Linear Regression)

Actions that create an entire copy of the data file in temporary disk space include:

 Reading Excel files

 Running procedures that sort data (for example, Sort Cases, Split File)

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Chapter 3

Reading data with GET TRANSLATE or DATA LIST commands



 Using the Cache Data facility or the CACHE command

 Launching other applications from SPSS that read the data file (for example,

AnswerTree, DecisionTime)

Note:TheGET DATA command provides functionality comparable to DATA LIST
without creating an entire copy of the data file in temporary disk space. The SPLIT

FILE

command in command syntax does not sort the data file and therefore does
not create a copy of the data file. This command, however, requires sorted data for
proper operation, and the dialog box interface for this procedure will automatically
sort the data file, resulting in a complete copy of the data file. (Command syntax is
not available with the Student Version.)

Actions that create an entire copy of the data file by default:

 Reading databases with the Database Wizard

 Reading text files with the Text Wizard

The Text Wizard provide an optional setting to automatically cache the data. By
default, this option is selected. You can turn it off by deselecting

Cachedatalocally.

For the Database Wizard you can paste the generated command syntax and delete the

CACHE command.

Creating a Data Cache

Although the virtual active file can vastly reduce the amount o f temporary disk space
required, the absence of a temporary copy of the “active” file means that the original
data source has to be reread for each procedure. For large data files read f rom an
external source, creating a temporary copy of the data may improve performance. For
example, for data tables read from a database source, the SQL query that reads the
information from the database must be reexecuted for any command or procedure that
needs to read the data. Since virtually all statistical analysis procedures and charting
procedures need to read the data, the SQL query is reexecuted for each procedure you
run, which can result in a significant increase in processing time if you run a large
number of procedures.

If you have sufficient disk space on the computer performing the analysis (either
your local computer or a remote server), you can eliminate multiple SQL queries and
improve processing time by creating a data cache of the active file. The data cache is
a temporary copy of the complete data.

Note: By default, the Database Wizard automatically creates a data cache, but if you
use the

GET DATA command in command syntax to read a database, a data cache is not

automatically created. (Command syntax is not available with the Student Version.)

To Create a Data Cache

E From the menus choose:

File

Cache Data...

E

Click OK or Cache Now.

OK creates a data cache the next time the program reads the data (for example, the

next time you run a statistical procedure), which is usually what you want because it
doesn’t require an extra data pass.

Cache Now creates a data cache immediately, which

shouldn’t be necessary under most circumstances. Cache Now is useful primarily for
two reasons:

 A data source is “locked” and can’t be updated by anyone until you end your

session, open a different data source, or cache the data.

 For large data sources, scrolling through the contents of the Data View tab in the

Data Editor will be much faster if you cache the data.

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Data Files

To Cache Data Automatically

You can use the SET command to automatically create a data cache after a specified
number of changes in the active data file. By default, the active data file is
automatically cached after 20 changes in the active data file.

E From the menus choose:

File

New

Syntax

E

In the syntax window, type SET CACHE n. (where n represents the number of changes
in the active data file before the data file is cached).

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Chapter 3

From the menus in the syntax window choose:

E

Run

All

Note: The cache setting is not persistent across sessions. Each time you start a new
session, the value is reset to the default of 20.

Distributed Analysis Mode

Distributed analysis mode allows you to use a computer other than your local (or
desktop) computer for memory-intensive work. Because remote servers that are
used for distributed analysis are typically more powerful and faster than your local
computer, distributed analysis mode can significantly reduce computer processing
time. Distributed analysis with a remote server can be useful if your work involves:

 Large data files, particularly data that are read from database sources.

 Memory-intensive tasks. Any task that takes a long time in local analysis mode

might be a good candidate for distributed analysis.

Distributed analysis affects only data-related tasks, such as reading data, transforming
data, computing new variables, and calculating statistics. Distributed analysis has no
effect on tasks that are related to editing output, such as manipulating pivot tables or
modifying charts.

Chapter

4

Note: Distributed analysis is available only if you have both a local version and access
to a licensed server version of the software that is installed on a remote server.

Distributed A nalysis versus Local Analysis

Following are some guidelines for choosing distributed analysis or local analysis mode:

Database access. Jobs that perform database queries may run faster in distributed mode

if the server has superior access to the database or if the server is running on the same
machine as the database engine. Additionally, if the necessary database-access software
is available only on the server, or if your network administrator does not permit you to
download large data tables, you can access the database only in d istributed mode.

Ratio of computation to output. Commands that have the most to gain from running in

distributed mode are commands that perform a lot of computation and produce small
output results (for example, few and small pivot tables, brief text results, or few and

73

74

Chapter 4

simple charts). The degree of improvement depends largely on the computing power of
theremoteserver.

Small jobs. Jobs that run quickly in local mode will almost always run slower in

distributed mode because of inherent client/server overhead.

Charts. Case-oriented charts, such as scatterplots, regression residual plots, and

sequence charts, require raw data on your local computer. For large data files or
database tables, this process can result in slower performance in distributed mode
because the data have to be sent from the remote server to your local computer. Other
charts are based on summarized or aggregated data and should perform adequately
because the aggregation is performed on the server.

Interactive graphics. If raw data is saved with interactive graphics (an optional setting),

large amounts of data may be transferred from the remote server to your local
computer, significantly increasing the time that it takes to save your results.

Pivot tables. Large pivot tables may take longer to create in distributed mode. This

situation is particularly true for the OLAP Cubes procedure and tables that contain
individual case data, such as those tables that are available in the Summarize procedure.

Text output. The more text that is produced, the slower output will be in distributed mode

because the text is produced on the remote server and copied to your local computer
for display. Text results have low overhead, however, and tend to transmit quickly.

Server Login

The Server Login dialog box allows you to select the computer that processes
commands and runs procedures. You can select your local computer or a remote server.