Applied multivariate statistics for the social sciences:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Mahwah, NJ [u.a.]
Erlbaum
2002
|
| Edition: | 4. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XIV, 703 S. graph. Darst. 1 CD-ROM (12 cm) |
| ISBN: | 0805837760 0805837779 |
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MARC
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Table of Contents
PREFACE xiii
Chapter 1 INTRODUCTION
1.1 Introduction 1
1.2 Type I Error, Type II Error, and Power 3
1.3 Multiple Statistical Tests and the
Probability of Spurious Results 6
1.4 Statistical Significance Versus
Practical Significance 9
1.5 Outliers 12
1.6 Research Examples for Some Analyses
Considered in This Text 17
1.7 The SAS and SPSS Statistical Packages 24
1.8 SPSS for Windows—Releases 9.0 and 10.0 34
1.9 Data Files 36
1.10 Data Editing 40
1.11 SPSS Output Navigator 45
1.12 Some Issues Unique to Multivariate Analysis 48
1.13 Data Collection and Integrity 49
Appendix 1: Defining a Measure of
Statistical Distance SO
Appendix 2: Milk Data 52
Exercises 53
Chapter 2 MATRIX ALGEBRA
2.1 Introduction 56
2.2 Addition, Subtraction, and Multiplication
of a Matrix by a Scalar 59
2.3 Obtaining the Matrix of Variances
and Covariances 62
2.4 Determinant of a Matrix 64
2.5 Inverse of a Matrix 70
2.6 Eigenvalues 73
2.7 SPSS Matrix Procedure 75
2.8 SAS IML Procedure 76
Exercises 77
Chapter 3 MULTIPLE REGRESSION
3.1 Introduction 80
3.2 Simple Regression 82
3.3 Multiple Regression for Two
Predictors—Matrix Formulation 86
3.4 Mathematical Maximization Nature
of Least Squares Regression 88
3.5 Breakdown of Sum of Squares in
Regression and F Test for Multiple Correlation 89
3.6 Relationship of Simple Correlations
to Multiple Correlation 91
3.7 Multicollinearity 91
3.8 Model Selection 93
3.9 Two Computer Examples 98
3.10 Checking Assumptions for the
Regression Model 110
3.11 Model Validation 113
3.12 Importance of the Order of the
Predictors in Regression Analysis 119
3.13 Other Important Issues 121
3.14 Outliers and Influential Data Points 125
3.15 Further Discussion of the Two
Computer Examples 138
3.16 Sample Size Determination for a
Reliable Prediction Equation 143
3.17 Logistic Regression 146
3.18 Other Types of Regression Analysis 155
3.19 Multivariate Regression 155
3.20 Summary of Important Points 159
Exercises 161
Chapter 4 TWO GROUP MULTIVARIATE ANALYSIS
OF VARIANCE
4.1 Introduction 173
4.2 Four Statistical Reasons for Preferring
a Multivariate Analysis 174
4.3 The Multivariate Test Statistic as a
Generalization of Univariate t 175
4.4 Numerical Calculations for a
Two Group Problem 177
4.5 Three Post Hoc Procedures 181
4.6 SAS and SPSS Control Lines for Sample
Problem and Selected Printout 183
4.7 Multivariate Significance but No Univariate
Significance 184
4.8 Multivariate Regression Analysis
for the Sample Problem 188
4.9 Power Analysis 192
4.10 Ways of Improving Power 195
4.11 Power Estimation on SPSS MANOVA 197
4.12 Multivariate Estimation of Power 197
4.13 Summary 202
Exercises 203
Chapter 5 # GROUP MANOVA: A PRIORI
AND POST HOC PROCEDURES
5.1 Introduction 208
5.2 Multivariate Regression Analysis for
a Sample Problem 209
5.3 Traditional Multivariate Analysis
of Variance 210
5.4 Multivariate Analysis of Variance
for Sample Data 212
5.5 Post Hoc Procedures 217
5.6 The Tukey Procedure 222
5.7 Planned Comparisons 225
5.8 Test Statistics for Planned Comparisons 228
5.9 Multivariate Planned Comparisons
on SPSS MANOVA 231
5.10 Correlated Contrasts 235
5.11 Studies Using Multivariate Planned
Comparisons 241
5.12 Stepdown Analysis 243
5.13 Other Multivariate Test Statistics 243
5.14 How Many Dependent Variables
for a MANOVA? 245
5.15 Power Analysis—A Priori Determination
of Sample Size 245
5.16 Summary 247
Appendix: Novince (1977) Data for Multivariate
Analysis of Variance Presented in
Tables 5.3 and 5.4 249
Exercises 250
Chapter 6 ASSUMPTIONS IN MANOVA
6.1 Introduction 256
6.2 ANOVA and MANOVA Assumptions 257
6.3 Independence Assumption 258
6.4 What Should Be Done With
Correlated Observations? 260
6.5 Normality Assumption 261
6.6 Multivariate Normality 262
6.7 Assessing Univariate Normality 263
6.8 Homogeneity of Variance Assumption 268
6.9 Homogeneity of the Covariance Matrices 269
6.10 General Procedure for Assessing
Violations in MANOVA 276
Appendix: Multivariate Test Statistics
for Unequal Covariance Matrices 279
Exercises 280
Chapter 7 DISCRIMINANT ANALYSIS
7.1 Introduction 285
7.2 Descriptive Discriminant Analysis 286
7.3 Significance Tests 287
7.4 Interpreting the Discriminant Functions 288
7.5 Graphing the Groups in the Discriminant
Plane 289
7.6 Rotation of the Discriminant Functions 296
7.7 Stepwise Discriminant Analysis 296
7.8 Two Other Studies That Used Discriminant
Analysis 297
7.9 The Classification Problem 301
7.10 Linear vs. Quadratic Classification Rule 316
7.11 Characteristics of a Good Classification
Procedure 316
7.12 Summary of Major Points 317
Exercises 318
Chapter 8 FACTORIAL ANALYSIS OF VARIANCE
8.1 Introduction 321
8.2 Advantages of a Two Way Design 322
8.3 Univariate Factorial Analysis 324
8.4 Factorial Multivariate Analysis of Variance 331
8.5 Weighting of the Cell Means 332
8.6 Three Way MANOVA 335
Exercises 336
Chapter 9 ANALYSIS OF COVARIANCE
9.1 Introduction 339
9.2 Purposes of Covariance 340
9.3 Adjustment of Posttest Means and
Reduction of Error Variance 342
9.4 Choice of Covariates 345
9.5 Assumptions in Analysis of Covariance 347
9.6 Use of ANCOVA With Intact Groups 350
9.7 Alternative Analyses for Pretest
Posttest Designs 351
9.8 Error Reduction and Adjustment of
Posttest Means for Several Covariates 353
9.9 MANCOVA—Several Dependent Variables
and Several Covariates 354
9.10 Testing the Assumption of Homogeneous
Regression Hyperplanes on SPSS 355
9.11 Two Computer Examples 356
9.12 Bryant Paulson Simultaneous
Test Procedure 361
9.13 Summary of Major Points 366
Exercises 367
Chapter 10 STEPDOWN ANALYSIS
10.1 Introduction 374
10.2 Four Appropriate Situations for
Stepdown Analysis 375
10.3 Controlling on Overall Type I Error 376
10.4 Stepdown Fs for Two Groups 377
10.5 Comparison of Interpretation of
Stepdown Fs vs. Univariate Fs 379
10.6 Stepdown Fs for k Groups—Effect of
Within and Between Correlations 381
10.7 Summary 383
Chapter 11 CONFIRMATORY AND EXPLORATORY
FACTOR ANALYSIS
11.1 Introduction 385
11.2 The Nature of Principal Components 386
11.3 Three Uses for Components as a
Variable Reducing Scheme 388
11.4 Criteria for Deciding on How Many
Components to Retain 389
11.5 Increasing Interpretability of Factors
by Rotation 391
11.6 What Loadings Should Be Used for
Interpretation? 393
11.7 Sample Size and Reliable Factors 395
11.8 Four Computer Examples 395
11.9 The Communality Issue 409
11.10 A Few Concluding Comments 410
11.11 Exploratory and Confirmatory
Factor Analysis 411
11.12 PRELIS 415
11.13 A LISREL Example Comparing Two A
Priori Models 419
11.14 Identification 427
11.15 Estimation 429
11.16 Assessment of Model Fit 430
11.17 Model Modification 435
11.18 LISREL 8 Example 437
11.19 EQS Example 445
11.20 Some Caveats Regarding Structural
Equation Modeling 449
Exercises 454
Chapter 12 CANONICAL CORRELATION
12.1 Introduction 471
12.2 The Nature of Canonical Correlation 472
12.3 Significance Tests 473
12.4 Interpreting the Canonical Variates 475
12.5 Computer Example Using SAS
CANCORR 476
12.6 A Study That Used Canonical
Correlation: Relationship Between
Student Needs and Teacher Ratings 479
12.7 Using SAS for Canonical Correlation
on Two Sets of Factor Scores 481
12.8 The Redundancy Index of Stewart and Love 483
12.9 Rotation of Canonical Variates 485
12.10 Obtaining More Reliable Canonical Variates 485
12.11 Summary 486
Exercises 487
Chapter 13 REPEATED MEASURES ANALYSIS
13.1 Introduction 492
13.2 Single Group Repeated Measures 496
13.3 The Multivariate Test Statistic for
Repeated Measures 497
13.4 Assumptions in Repeated Measures
Analysis 500
13.5 Computer Analysis of the Drug Data 502
13.6 Post Hoc Procedures in Repeated
Measures Analysis 506
13.7 Should We Use the Univariate or
Multivariate Approach? 509
13.8 Sample Size for Power = .80 in
Single Sample Case 510
13.9 Multivariate Matched Pairs Analysis 512
13.10 One Between and One Within Factor—A
Trend Analysis 512
13.11 Post Hoc Procedures for the One
Between and One Within Design 519
13.12 One Between and Two Within Factors 521
13.13 Two Between and One Within Factors 526
13.14 Two Between and Two Within Factors 532
13.15 Totally Within Designs 532
13.16 Planned Comparisons in Repeated
Measures Designs 534
13.17 Profile Analysis 536
13.18 Doubly Multivariate Repeated Measures
Designs 538
13.19 Summary of Major Points 544
Exercises 552
Chapter 14 CATEGORICAL DATA ANALYSIS:
THE LOG LINEAR MODEL
14.1 Introduction 558
14.2 Sampling Distributions: Binomial
and Multinomial 561
14.3 Two Way Chi Square—Log Linear Formulation 564
14.4 Three Way Tables 567
14.5 Model Selection 576
14.6 Collapsibility 578
14.7 The Odds (Cross Product) Ratio 582
14.8 Normed Fit Index and Residual Analysis 583
14.9 Residual Analysis 584
14.10 Cross Validation 585
14.11 Higher Dimensional Tables—
Model Selection
14.12 Contrasts for the Log Linear Model 586
14.13 Log Linear Analysis for Ordinal Data 590
14.14 Sampling and Structural (Fixed) Zeros 595
Exercises 596
References 603
Appendix A: Statistical Tables 614
Appendix B: Data Sets 634
Appendix C: Obtaining Nonorthogonal
Contrasts in Repeated
Measures Designs 653
Answer Section 661
Author Index 689
Subject Index 693 |
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| dewey-tens | 510 - Mathematics |
| discipline | Soziologie Psychologie Mathematik Wirtschaftswissenschaften |
| edition | 4. ed. |
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| language | English |
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| spelling | Stevens, James Verfasser (DE-588)122981898 aut Applied multivariate statistics for the social sciences James Stevens 4. ed. Mahwah, NJ [u.a.] Erlbaum 2002 XIV, 703 S. graph. Darst. 1 CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier Sozialwissenschaften (DE-588)4055916-6 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 s Sozialwissenschaften (DE-588)4055916-6 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009593808&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Stevens, James Applied multivariate statistics for the social sciences Sozialwissenschaften (DE-588)4055916-6 gnd Multivariate Analyse (DE-588)4040708-1 gnd |
| subject_GND | (DE-588)4055916-6 (DE-588)4040708-1 |
| title | Applied multivariate statistics for the social sciences |
| title_auth | Applied multivariate statistics for the social sciences |
| title_exact_search | Applied multivariate statistics for the social sciences |
| title_full | Applied multivariate statistics for the social sciences James Stevens |
| title_fullStr | Applied multivariate statistics for the social sciences James Stevens |
| title_full_unstemmed | Applied multivariate statistics for the social sciences James Stevens |
| title_short | Applied multivariate statistics for the social sciences |
| title_sort | applied multivariate statistics for the social sciences |
| topic | Sozialwissenschaften (DE-588)4055916-6 gnd Multivariate Analyse (DE-588)4040708-1 gnd |
| topic_facet | Sozialwissenschaften Multivariate Analyse |
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