spss' for windows' advanced statistics release 6
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SPSS' for Windows'Advanced StatisticsRelease 6.0
Mariju J. Narusis! SPSS Inc.
SPSS Inc.444 N. Michigan AvenueChicago, Illinois 60611Tel: 1312) 329-2400Fax: (312i 329-3668
SPSS Federal Systems [U.S.)SPSS Latin AmericaSPSS Benelux BVSPSS UK Ltd.SPSS UK Ltd.. New DelhiSPSS GmbH SoftwareSPSS Scandinavia AHSPSS Ania Pacific Pte. Ltd.SPSS Japan Inc.SPSS Australasia Pty. Lid.
SportbibliothekTU Darmstadt
61725709
1 Logistic Regression Analysis 1The Logistic Regression Model 2
An Example 3Coefficients for the Logistic Model 4Interpreting the. Regression Coefficients 6Assessing the Goodness of Fit of the Model 7Categorical Variables 11Interaction Terms 14Selecting Predictor Variables 14Diagnostic Methods 19
How to Obtain a Logistic Regression Analysis 23Selecting a Subset of Cases for Analysis 25Defining Categorical Variables 26
.̂ Saving New Variables 27Options 28Additional Features Available with Command Syntax 30
2 General Factorial Analysis of Variance 31A Simple Factorial Design * 31
Where Are We? . 32.Describing the Data 33Equality of Variances 35The Analysis-of-Variance Table 36Full Factorial Model 37Examining Contrasts 37 •*%Simple Contrasts 39The Problem of Multiple Comparisons 40Measuring Effect Size 41Power Computations 41Examining Residuals 42 »
An Analysis-of-Covariance Model 44Testing for Equal Slopes 45
VII
The Analysis-of-Covariance Table 46More Than One Factor 48Types of Sums of Squares 48
How to Obtain a General Factorial Analysis of Variance 48Defining Levels o^Factor Variables 50Specifying Contrasts 50Specifying the MANOVA Model 52Options 55 ;Additional Features Available with Command Syntax 56
Multivariate Analysis of Variance 57Multivariate Analysis of Variance 58
Assumptions 58One-Sample Hotelling's T2 59Descriptive Statistics 60Further Displays for Checking Assumptions 61Testing Hypotheses 67Univariate Tests 69The Two-Sample Multivariate T Test 69
- ~~A Multivariate Factorial Design 79
How to Obtain a Multivariate Analysis of Variance 96Defining Levels of Factor Variables 97Specifying Contrasts 98Specifying the MANOVA Model 100Options 103Additional Features Available with Command Syntax 105
Repeated Measures Analysis of Variance 107Repeated Measures 107 •
Describing the Data 108Analyzing Differences 110Testing for Differences 112Choosing Multivariate or Univariate Results 116Selecting Other Contrasts 117Adding Another Factor 118Testing Hypotheses 120
VIII
Within-Subjects and Between-Subjects Factors 124Analysis of Covariance with a Constant Covariate 129Doubly Multivariate Repeated Measures Designs 132
How to Obtain a Repeated Measures ANOVA 132Doubly Multivariate Repeated Measures 133Within-Subject Variables and Between-Subjects Factors 134Co.variates 135Contrasts 137Specifying the Model 140Options 142Additional Features Available with Command Syntax 144
Hierarchical Loglinear Models 145Loglinear Models 146
A Fully Saturated Model 146The Independence Model 152Hierarchical Models 156Model Selection 157Partitioning the Chi-square Statistic 157Testing Individual Terms in the Model 160Model Selection Using Backward Elimination 162
SPSS Loglinear Analysis Procedures 164
How to Obtain a Hierarchical Loglinear Analysis 164Defining Factor Ranges • 165
, Model Specification 165Options' 167Additional Features Available with Command Syntax 169
Further Topics in Loglinear Models 171. •Loglinear Models 171 **
Frequency Table Models 171Fitting a Logit Model 175Fitting an Unsaturated Logit Model 180Fitting a More Complicated Logit ModelThe Equivalent Loglinear Model 184
Models for Ordinal Data 184The Linear-by-Linear Association Model 186Row^ and Column-Effects Models 187
Incomplete Tables 189Testing Real agaiast Ideal 189•Quasi-lndependerice 190Symmetry Models 191Adjusted Quasj-Symmetry 195
An Ordinal Model for Real versus Ideal 196Parameter Estimates 197The Design Matrix 199
SPSS Loglinear Analysis Procedures 201
How to Obtain a General Loglinear Analysis 201.,Defining Factor Ranges 202Contrast Specification 203Model Specification 204Options 206Additional Features Available with Command Syntax 207
How to Obtain a Logit Loglinear Analysis 207_Defining Ranges of Categorical Variables 209
Contrast Specification 209Model Specification .210Options 212Additional Features Available with Command Syntax 213
Nonlinear Regression 215What Is a Nonlinear Model? 215
Transforming Nonlinear Models 216Intrinsically Nonlinear Models 217Fitting the Logistic Population Growth Model 217Estimating Starting Values 222Computational Problems • 224Additional Nonlinear Regression Options 224
How to Obtain a Nonlinear Regression Analysis 224Defining Model Parameters 226Defining a Loss Function 227Specifying Parameter Constraints 228Saving New Variables 229Options 229Additional Features Available with Command Syntax 232
8 Probit Analysis 233Probit and Logit Response Models 233
An Example 234Comparing Several Groups 237Comparing Relative Potencies of the Agents 239Estimating the Natural Response Rate 241More than One Stimulus Variable 241
How to Obtain a. Probit Analysis 241Defining Factor Range 243
v- Options 244Additional Features Available with Command Syntax 246
9 Life Tables 247The Follow-up Life Table 247
A Personnel Example 247, Assumptions Needed to Use the Life Table 251
Lost to Follow-up 252Plotting Survival Functions 252Comparing Survival Functions 253
How to Obtain Life Tables^ 253Define Event for Status Variable 255Define Range for Factor Variable 255Options 256Additional Features Available with Command Syntax .257
XI
Kaplan-Meier Survival Analysis 259Kaplan-Meier Estimators 259
The SPSS Kaplan-Meier Table 261Plotting the Cumulative Survival 263
Comparing Survival Functions 263Stratified Comparisons of Survival Functions 266
How to Obtain a. Kaplan-Meier Survival Analysis 268Define EvenHor Status Variable 270Comparing Factor Levels -270Saving New Variables 272Options 272Additional Features Available with Command Syntax 273
Cox Regression 275The Cox Regression Model 275
The Hazard Function 277Multiple Covariates .279Testing the Model 281
-Select[ng_Predi.ctor Variables 282Plotting the Estimated Functions 287Checking the. Proportional Hazards Assumption 288Time-Dependent Covariates 289
Graphical Displays 291Looking for Influential Cases 292Examination of Residuals 293
SPSS Cox Regression Procedures 295
How to Obtain a Time-Constant Cox Regression Analysis 295Define Event for Status Variable 298Defining Categorical Predictors - 298Plots 300Saving'New Variables 301Options 302Additional Features Available with Command Syntax 303
XII
How to Obtain a Time-Dependent Cox Regression Analysis 304Defining the Time-Dependent Cox Regression Model 305Define Event for Status Variable 307Defining Categorical Predictors 308Saving the Change in Regression Coefficients 310Options 310Additional Features Available with Command Syntax 312
Writing Your Own Program: The Matrix Language 313Nearest-Neighbor Discriminant Analysis 313
The Matrix Job 314
Repeated Measures Analysis of Categorical Data 318The Matrix Job 320
Using the Matrix Language 322Using Matrix Commands in a Syntax Window 323
Syntax ReferenceIntroduction 327
COXREG 333
HILOGLINEAR 347
KM 356
LOGISTIC REGRESSION 365
L 6 G L I N E " A R " ~ 3 7 8
MANOVA: Overview 391
MANOVA: Univariate 394
MANOVA: Multivariate 420
MANOVA: Repeated Measures 433
MATRIX—END MATRIX 442
NLR 487
PROBIT 503
SURVIVAL 512
XIII
Appendix AMatrix Macros 525Limitations of Macros 525
Using the Macros »526
Canonical Correlation 527Using the CANCORR Macro 530
Discriminant Holdout Classification 531Using the DISCLASS Macro 533
Ridge Regression 534Using the RIDGEREG Macro 536
Appendix BCategorical Variable Coding Schemes 539
Deviation 539Simpje 540Helmert 541Difference 541Polynomial 542RepeafecT 543Special 543Indicator 544
Bibliography 545
Subject Index 551
Syntax Index 567
XIV
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