Performing Data Analysis Using IBM SPSS

733 Pages·2013·46.84 MB·English

by  Lawrence S. Meyers

PERFORMING DATA ANALYSIS
USING IBM SPSS
PERFORMING DATA ANALYSIS

USING IBM SPSS
LAWRENCE S. MEYERS
DepartmentofPsychology
CaliforniaStateUniversity,Sacramento
Sacramento,California
GLENN C. GAMST
DepartmentofPsychology
UniversityofLaVerne
LaVerne,California
A. J. GUARINO
DepartmentofBiostatistics
MGHInstituteofHealthProfessions
Boston,Massachusetts
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LibraryofCongressCataloging-in-PublicationData:
Meyers,LawrenceS.
PerformingdataanalysisusingIBMSPSS/ LawrenceS.Meyers,DepartmentofPsychology,California
StateUniversity,Sacramento,Sacramento,CA,GlennC.Gamst,DepartmentofPsychology,UniversityofLa
Verne,LaVerne,CA,A.J.Guarino,DepartmentofBiostatistics,MGHInstituteofHealthProfessions,
Boston,MA.
pagescm
Includesbibliographicalreferencesandindex.
ISBN978-1-118-35701-9(pbk.)–ISBN978-1-118-51494-8–ISBN978-1-118-51492-4(ePDF)–ISBN
978-1-118-51493-1(ePub)–ISBN978-1-118-51490-01.Socialsciences–Statisticalmethods–Computer
programs.2.SPSS(Computerfile)I.Title.
HA32.M49942013
005.5’5–dc23
2013002844
PrintedintheUnitedStatesofAmerica
10987654321
CONTENTS
PREFACE ix
PART1 | GETTINGSTARTEDWITHIBMSPSS 1
CHAPTER1 | INTRODUCTIONTOIBMSPSS 3
CHAPTER2 | ENTERINGDATAINIBMSPSS 5
CHAPTER3 | IMPORTINGDATAFROMEXCELTOIBMSPSS 15
PART2 | OBTAINING,EDITING,ANDSAVINGSTATISTICAL
OUTPUT 19
CHAPTER4 | PERFORMINGSTATISTICALPROCEDURES
INIBMSPSS 21
CHAPTER5 | EDITINGOUTPUT 27
CHAPTER6 | SAVINGANDCOPYINGOUTPUT 31
PART3 | MANIPULATINGDATA 37
CHAPTER7 | SORTINGANDSELECTINGCASES 39
CHAPTER8 | SPLITTINGDATAFILES 45
CHAPTER9 | MERGINGDATAFROMSEPARATEFILES 51
PART4 | DESCRIPTIVESTATISTICSPROCEDURES 57
CHAPTER10 | FREQUENCIES 59
CHAPTER11 | DESCRIPTIVES 67
CHAPTER12 | EXPLORE 71
PART5 | SIMPLEDATATRANSFORMATIONS 77
CHAPTER13 | STANDARDIZINGVARIABLESTOZSCORES 79
CHAPTER14 | RECODINGVARIABLES 83
CHAPTER15 | VISUALBINNING 97
v
vi CONTENTS
CHAPTER16 | COMPUTINGNEWVARIABLES 103
CHAPTER17 | TRANSFORMINGDATESTOAGE 111
PART6 | EVALUATINGSCOREDISTRIBUTION
ASSUMPTIONS 121
CHAPTER18 | DETECTINGUNIVARIATEOUTLIERS 123
CHAPTER19 | DETECTINGMULTIVARIATEOUTLIERS 131
CHAPTER20 | ASSESSINGDISTRIBUTIONSHAPE:NORMALITY,
SKEWNESS,ANDKURTOSIS 139
CHAPTER21 | TRANSFORMINGDATATOREMEDYSTATISTICAL
ASSUMPTIONVIOLATIONS 147
PART7 | BIVARIATECORRELATION 157
CHAPTER22 | PEARSONCORRELATION 159
CHAPTER23 | SPEARMANRHOANDKENDALLTAU-BRANK-ORDER
CORRELATIONS 165
PART8 | REGRESSING(PREDICTING)QUANTITATIVE
VARIABLES 171
CHAPTER24 | SIMPLELINEARREGRESSION 173
CHAPTER25 | CENTERINGTHEPREDICTORVARIABLEINSIMPLE
LINEARREGRESSION 181
CHAPTER26 | MULTIPLELINEARREGRESSION 191
CHAPTER27 | HIERARCHICALLINEARREGRESSION 211
CHAPTER28 | POLYNOMIALREGRESSION 217
CHAPTER29 | MULTILEVELMODELING 225
PART9 | REGRESSING(PREDICTING)CATEGORICAL
VARIABLES 253
CHAPTER30 | BINARYLOGISTICREGRESSION 255
CHAPTER31 | ROCANALYSIS 265
CHAPTER32 | MULTINOMINALLOGISTICREGRESSION 273
PART10 | SURVIVALANALYSIS 281
CHAPTER33 | SURVIVALANALYSIS:LIFETABLES 283
CHAPTER34 | THEKAPLAN–MEIERSURVIVALANALYSIS 289
CHAPTER35 | COXREGRESSION 301
CONTENTS vii
PART11 | RELIABILITYASAGAUGEOFMEASUREMENT
QUALITY 309
CHAPTER36 | RELIABILITYANALYSIS:INTERNALCONSISTENCY 311
CHAPTER37 | RELIABILITYANALYSIS:ASSESSINGRATERCONSISTENCY 319
PART12 | ANALYSISOFSTRUCTURE 329
CHAPTER38 | PRINCIPALCOMPONENTSANDFACTORANALYSIS 331
CHAPTER39 | CONFIRMATORYFACTORANALYSIS 353
PART13 | EVALUATINGCAUSAL(PREDICTIVE)MODELS 379
CHAPTER40 | SIMPLEMEDIATION 381
CHAPTER41 | PATHANALYSISUSINGMULTIPLEREGRESSION 389
CHAPTER42 | PATHANALYSISUSINGSTRUCTURALEQUATION
MODELING 397
CHAPTER43 | STRUCTURALEQUATIONMODELING 419
PART14 | t TEST 457
CHAPTER44 | ONE-SAMPLEt TEST 459
CHAPTER45 | INDEPENDENT-SAMPLESt TEST 463
CHAPTER46 | PAIRED-SAMPLESt TEST 471
PART15 | UNIVARIATEGROUPDIFFERENCES:ANOVAAND
ANCOVA 475
CHAPTER47 | ONE-WAYBETWEEN-SUBJECTSANOVA 477
CHAPTER48 | POLYNOMIALTRENDANALYSIS 485
CHAPTER49 | ONE-WAYBETWEEN-SUBJECTSANCOVA 493
CHAPTER50 | TWO-WAYBETWEEN-SUBJECTSANOVA 507
CHAPTER51 | ONE-WAYWITHIN-SUBJECTSANOVA 521
CHAPTER52 | REPEATEDMEASURESUSINGLINEARMIXEDMODELS 531
CHAPTER53 | TWO-WAYMIXEDANOVA 555
PART16 | MULTIVARIATEGROUPDIFFERENCES:MANOVA
ANDDISCRIMINANTFUNCTIONANALYSIS 567
CHAPTER54 | ONE-WAYBETWEEN-SUBJECTSMANOVA 569
CHAPTER55 | DISCRIMINANTFUNCTIONANALYSIS 579
CHAPTER56 | TWO-WAYBETWEEN-SUBJECTSMANOVA 591
viii CONTENTS
PART17 | MULTIDIMENSIONALSCALING 603
CHAPTER57 | MULTIDIMENSIONALSCALING:CLASSICALMETRIC 605
CHAPTER58 | MULTIDIMENSIONALSCALING:METRICWEIGHTED 613
PART18 | CLUSTERANALYSIS 621
CHAPTER59 | HIERARCHICALCLUSTERANALYSIS 623
CHAPTER60 | K-MEANSCLUSTERANALYSIS 631
PART19 | NONPARAMETRICPROCEDURESFOR
ANALYZINGFREQUENCYDATA 643
CHAPTER61 | SINGLE-SAMPLEBINOMIALANDCHI-SQUARETESTS:
BINARYCATEGORIES 645
CHAPTER62 | SINGLE-SAMPLE(ONE-WAY)MULTINOMINAL
CHI-SQUARETESTS 655
CHAPTER63 | TWO-WAYCHI-SQUARETESTOFINDEPENDENCE 665
CHAPTER64 | RISKANALYSIS 675
CHAPTER65 | CHI-SQUARELAYERS 681
CHAPTER66 | HIERARCHICALLOGLINEARANALYSIS 689
APPENDIX | STATISTICSTABLES 699
REFERENCES 703
AUTHORINDEX 713
SUBJECTINDEX 715
PREFACE
TheIBMSPSSsoftwarepackageisoneofthemostwidelyusedstatisticalapplications
inacademia,business,andgovernment.Thisbook,PerformingDataAnalysisUsingIBM
SPSS, provides readers with both a gentle introduction to basic statistical computation
with the IBM SPSS software package and a portal to the more comprehensive and
statistically robust multivariate procedures. This book was written to be a stand-alone
resource as well as a supplementary text for both undergraduate introductory and more
advanced graduate-level statistics courses.
For most of the chapters, we provide a consistent structure that includes the follow-
ing:
• Overview: This is a brief conceptual introduction that furnishes a set of rele-
vant details for each statistical procedure being covered, including a few useful
references that supply additional background information.
• NumericalExample: This includes a description of the research problem or ques-
tion, the name of the data file, a description of the variables and how they are
coded, and (often) a screenshot of the IBM SPSS Data View.
• Analysis Strategy: When the analysis is performed in stages, or when alternative
data processing strategies are available, we include a description of how we have
structured our data analysis and explain the rationale for why we have performed
the analyses in the way presented in the chapter.
• AnalysisSetup: This includes how to configure each dialog window with screen-
shots and is accompanied (within reason) with explanations for why we chose the
particular options we utilized.
• Analysis Output: This elucidates the major aspects of the statistical output with
pertinent screenshots and discussion.
Becauseofthemultipleaudienceweareattemptingtoreachwiththisbook,thecom-
plexity of the procedures covered varies substantially across the chapters. For example,
chapters that cover IBM SPSS basics of data entry and file manipulation, descriptive
statistical procedures, correlation, simple linear regression, multiple regression, one-way
chi-square, t tests, and one and two-way analysis of variance designs are all appro-
priate topics for first- or second-level statistics and data analysis courses. The remain-
ing chapters, data transformations, assumption violation assessment, reliability analysis,
logistic regression, multivariate analysis of variance, survival analysis, multidimensional
scaling, cluster analysis, multilevel modeling, exploratory and confirmatory factor anal-
ysis, and structural equation modeling, are all important topics that may be suitable for
more advanced statistics courses.
There are 66 chapters in this book. They are organized into 19 sections or “Parts.”
Different authors might organize the chapters in somewhat different ways and present
them in a somewhat different order, as there is no fully agreed upon organizational
structure for this material. However, except for the chapters presented in the early parts
that show readers how to work with IBM SPSS data files, most of the data analysis
chapters can be used as a resource on their own, allowing users to work with whatever
analysisproceduresmeettheirneeds;theorderinwhichuserswouldchoosetoworkwith
ix