Verfügbarkeit: Applied multivariate statistics for the social sciences

Applied multivariate statistics for the social sciences:

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Bibliographische Detailangaben
1. Verfasser:	Stevens, James (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	New York, NY [u.a.] Routledge 2009
Ausgabe:	5. ed.
Schlagworte:	Sozialwissenschaften Multivariate analysis Social sciences > Statistical methods Multivariate Analyse
Online-Zugang:	Inhaltsverzeichnis
Beschreibung:	Includes bibliographical references
Beschreibung:	XII, 651 S. graph. Darst.
ISBN:	9780805859010 9780805859034

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adam_text	Contents Preface ..............................................................................................................................................xi 1 Introduction .............................................................................................................................1 1.1 Introduction ...................................................................................................................1 1.2 Type I Error, Type II Error, and Power .......................................................................2 1.3 Multiple Statistical Tests and the Probability of Spurious Results ........................5 1.4 Statistical Significance versus Practical Significance ...............................................8 1.5 Outliers .........................................................................................................................10 1.6 Research Examples for Some Analyses Considered in This Text ........................15 1.7 The SAS and SPSS Statistical Packages ....................................................................17 1.8 SPSS for Windows—Releases 15.0 and 16.0.............................................................26 1.9 Data Files ......................................................................................................................27 1.10 Data Editing .................................................................................................................28 1.11 SPSS Output Navigator ..............................................................................................34 1.12 Data Sets on the Internet ............................................................................................36 1.13 Importing a Data Set into the Syntax Window of SPSS ........................................36 1.14 Some Issues Unique to Multivariate Analysis ........................................................37 1.15 Data Collection and Integrity ....................................................................................38 1.16 Nonresponse in Survey Research .............................................................................39 1.17 Internal and External Validity ..................................................................................39 1.18 Conflict of Interest .......................................................................................................40 1.19 Summary ......................................................................................................................41 1.20 Exercises .......................................................................................................................41 2 Matrix Algebra ......................................................................................................................43 2.1 Introduction .................................................................................................................43 2.2 Addition, Subtraction, and Multiplication of a Matrix by a Scalar ......................46 2.3 Obtaining the Matrix of Variances and Covariances ............................................49 2.4 Determinant of a Matrix ............................................................................................50 2.5 Inverse of a Matrix ......................................................................................................54 2.6 SPSS Matrix Procedure ...............................................................................................57 2.7 SAS IML Procedure ....................................................................................................59 2.8 Summary ......................................................................................................................59 2.9 Exercises .......................................................................................................................60 3 Multiple Regression .............................................................................................................63 3.1 Introduction .................................................................................................................63 3.2 Simple Regression .......................................................................................................64 3.3 Multiple Regression for Two Predictors: Matrix Formulation ..............................69 3.4 Mathematical Maximization Nature of Least Squares Regression .....................71 3.5 Breakdown of Sum of Squares and F Test for Multiple Correlation ....................71 3.6 Relationship of Simple Correlations to Multiple Correlation ...............................73 3.7 Multicollinearity ..........................................................................................................74 3.8 Model Selection ...........................................................................................................75 Contents 3.9 Two Computer Examples ...........................................................................................80 3.10 Checking Assumptions for the Regression Model ................................................90 3.11 Model Validation .........................................................................................................93 3.12 Importance of the Order of the Predictors ..............................................................98 3.13 Other Important Issues ............................................................................................100 3.14 Outliers and Influential Data Points ......................................................................103 3.15 Further Discussion of the Two Computer Examples ...........................................113 3.16 Sample Size Determination for a Reliable Prediction Equation .........................117 3.17 Logistic Regression ...................................................................................................120 3.18 Other Types of Regression Analysis ......................................................................127 3.19 Multivariate Regression ...........................................................................................128 3.20 Summary ....................................................................................................................131 3.21 Exercises .....................................................................................................................132 Two-Group Multivariate Analysis of Variance ............................................................145 4.1 Introduction ...............................................................................................................145 4.2 Four Statistical Reasons for Preferring a Multivariate Analysis ........................146 4.3 The Multivariate Test Statistic as a Generalization of Univariate t ...................147 4.4 Numerical Calculations for a Two-Group Problem .............................................148 4.5 Three Post Hoc Procedures .....................................................................................152 4.6 SAS and SPSS Control Lines for Sample Problem and Selected Printout .........154 4.7 Multivariate Significance But No Univariate Significance ..................................156 4.8 Multivariate Regression Analysis for the Sample Problem ................................158 4.9 Power Analysis ..........................................................................................................162 4.10 Ways of Improving Power .......................................................................................164 4.11 Power Estimation on SPSS MÁNOVA ...................................................................166 4.12 Multivariate Estimation of Power ...........................................................................166 4.13 Summary ....................................................................................................................170 4.14 Exercises .....................................................................................................................171 i K-Group MÁNOVA: A Priori and Post Hoc Procedures ...........................................177 5.1 Introduction ...............................................................................................................177 5.2 Multivariate Regression Analysis for a Sample Problem ....................................177 5.3 Traditional Multivariate Analysis of Variance ......................................................178 5.4 Multivariate Analysis of Variance for Sample Data .............................................181 5.5 Post Hoc Procedures ..................................................................................................184 5.6 The Tukey Procedure ................................................................................................189 5.7 Planned Comparisons ..............................................................................................192 5.8 Test Statistics for Planned Comparisons ...............................................................194 5.9 Multivariate Planned Comparisons on SPSS MÁNOVA ....................................197 5.10 Correlated Contrasts .................................................................................................202 5.11 Studies Using Multivariate Planned Comparisons ..............................................204 5.12 Stepdown Analysis ...................................................................................................206 5.13 Other Multivariate Test Statistics ............................................................................207 5.14 How Many Dependent Variables for a Manova? ..................................................208 5.15 Power Analysis — A Priori Determination of Sample Size ...................................209 5.16 Summary... ....................................................................................................,............210 5.17 Exercises .....................................................................................................................211 Contents vii 6 Assumptions in MÁNOVA.............................................................................................. 217 6.1 Introduction ...............................................................................................................217 6.2 Anova and Mánova Assumptions ..........................................................................217 6.3 Independence Assumption ......................................................................................218 6.4 What Should Be Done with Correlated Observations? .......................................219 6.5 Normality Assumption ............................................................................................221 6.6 Multivariate Normality ............................................................................................222 6.7 Assessing Univariate Normality .............................................................................223 6.8 Homogeneity of Variance Assumption .................................................................227 6.9 Homogeneity oí the Covariance Matrices .............................................................228 6.10 Summary ....................................................................................................................234 Appendix 6.1: Analyzing Correlated Observations ........................................................236 Appendix 6.2: Multivariate Test Statistics for Unequal Covariance Matrices ............239 Exercises ................................................................................................................................241 7 Discriminant Analysis ......................................................................................................245 7.1 Introduction ...............................................................................................................245 7.2 Descriptive Discriminant Analysis ........................................................................245 7.3 Significance Tests ......................................................................................................247 7.4 Interpreting the Discriminant Functions ..............................................................248 7.5 Graphing the Groups in the Discriminant Plane .................................................248 7.6 Rotation of the Discriminant Functions ................................................................253 7.7 Stepwise Discriminant Analysis ............................................................................254 7.8 Two Other Studies That Used Discriminant Analysis ........................................254 7.9 The Classification Problem ......................................................................................258 7.10 Linear versus Quadratic Classification Rule .........................................................265 7.11 Characteristics of a Good Classification Procedure .............................................265 7.12 Summary ....................................................................................................................268 Exercises ................................................................................................................................269 8 Factorial Analysis of Variance .........................................................................................271 8.1 Introduction ...............................................................................................................271 8.2 Advantages of a Two-Way Design ..........................................................................271 8.3 Univariate Factorial Analysis ..................................................................................273 8.4 Factorial Multivariate Analysis of Variance ..........................................................280 8.5 Weighting of the Cell Means ...................................................................................281 8.6 Three-Way Mánova ...................................................................................................283 8.7 Summary ....................................................................................................................284 Exercises ................................................................................................................................285 9 Analysis of Covariance ......................................................................................................287 9.1 Introduction ...............................................................................................................287 9.2 Purposes of Covariance ...........................................................................................288 9.3 Adjustment of Posttest Means and Reduction of Error Variance ......................289 9.4 Choice of Covariates .................................................................................................292 9.5 Assumptions in Analysis of Covariance ...............................................................293 9.6 Use of ANCOVA with Intact Groups .....................................................................296 9.7 Alternative Analyses for Pretest-Posttest Designs ..............................................297 Contents 9.8 Error Reduction and Adjustment of Posttest Means for Several Covariates ......299 9.9 MANCOVA — Several Dependent Variables and Several Covariates ................299 9.10 Testing the Assumption of Homogeneous Hyperplanes on SPSS .....................300 9.11 Two Computer Examples .........................................................................................301 9.12 Bryant-Paulson Simultaneous Test Procedure .....................................................308 9.13 Summary ....................................................................................................................310 Exercises ................................................................................................................................310 10 Stepdown Analysis ............................................................................................................315 10.1 Introduction ...............................................................................................................315 10.2 Four Appropriate Situations for Stepdown Analysis ..........................................315 10.3 Controlling on Overall Type I Error .......................................................................316 10.4 Stepdown F s for Two Groups .................................................................................317 10.5 Comparison of Interpretation of Stepdown F s versus Univariate F s ..............319 10.6 Stepdown F s for К Groups — Effect of within and between Correlations ........321 10.7 Summary ....................................................................................................................322 11 Exploratory and Confirmatory Factor Analysis ...........................................................325 11.1 Introduction ...............................................................................................................325 11.2 Exploratory Factor Analysis ....................................................................................326 11.3 Three Uses for Components as a Variable Reducing Scheme ............................327 11.4 Criteria for Deciding on How Many Components to Retain ..............................328 11.5 Increasing Interpretability of Factors by Rotation ...............................................330 11.6 What Loadings Should Be Used for Interpretation? ............................................331 11.7 Sample Size and Reliable Factors ............................................................................333 11.8 Four Computer Examples ........................................................................................333 11.9 The Communality Issue ...........................................................................................343 11.10 A Few Concluding Comments ................................................................................344 11.11 Exploratory and Confirmatory Factor Analysis ...................................................345 11.12 PRELIS ........................................................................................................................348 11.13 A LISREL Example Comparing Two a priori Models ...........................................352 11.14 Identification ..............................................................................................................358 11.15 Estimation ..................................................................................................................359 11.16 Assessment of Model Fit ..........................................................................................360 11.17 Model Modification ..................................................................................................364 11.18 LISREL 8 Example .....................................................................................................367 11.19 EQS Example .............................................................................................................368 11.20 Some Caveats Regarding Structural Equation Modeling ...................................377 11.21 Summary ....................................................................................................................380 11.22 Exercises .....................................................................................................................381 12 Canonical Correlation ....................................................................,...................................395 12.1 Introduction ...............................................................................................................395 12.2 The Nature of Canonical Correlation .....................................................................396 12.3 Significance Tests ......................................................................................................397 12.4 Interpreting the Canonical Variâtes .......................................................................398 12.5 Computer Example Using SAS CANCORR ..........................................................399 12.6 A Study That Used Canonical Correlation ............................................................401 Contents ix 12.7 Using SAS for Canonical Correlation on Two Sets of Factor Scores ..................403 12.8 The Redundancy Index of Stewart and Love ........................................................405 12.9 Rotation of Canonical Variâtes ................................................................................406 12.10 Obtaining More Reliable Canonical Variâtes ........................................................407 12.11 Summary ....................................................................................................................408 12.12 Exercises .....................................................................................................................409 13 Repeated-Measures Analysis ...........................................................................................413 13.1 Introduction ...............................................................................................................413 13.2 Single-Group Repeated Measures ..........................................................................416 13.3 The Multivariate Test Statistic for Repeated Measures .......................................418 13.4 Assumptions in Repeated-Measures Analysis .....................................................420 13.5 Computer Analysis of the Drug Data ....................................................................422 13.6 Posi Hoc Procedures in Repeated-Measures Analysis .........................................425 13.7 Should We Use the Univariate or Multivariate Approach? ................................427 13.8 Sample Size for Power = .80 in Single-Sample Case ............................................429 13.9 Multivariate Matched Pairs Analysis .....................................................................429 13.10 One Between and One within Factor — A Trend Analysis ..................................432 13.11 Post Hoc Procedures for the One Between and One within Design ..................436 13.12 One Between and Two Within Factors ..................................................................438 13.13 Two Between and One Within Factors ..................................................................440 13.14 Two Between and Two Within Factors ..................................................................446 13.15 Totally Within Designs .............................................................................................447 13.16 Planned Comparisons in Repeated-Measures Designs ......................................449 13.17 Profile Analysis .........................................................................................................451 13.18 Doubly Multivariate Repeated-Measures Designs ..............................................455 13.19 Summary ....................................................................................................................456 13.20 Exercises .....................................................................................................................457 14 Categorical Data Analysis: The Log Linear Model .....................................................463 14.1 Introduction ...............................................................................................................463 14.2 Sampling Distributions: Binomial and Multinomial ...........................................465 14.3 Two-Way Chi-Square-Log Linear Formulation ...................................................468 14.4 Three-Way Tables ......................................................................................................471 14.5 Model Selection .........................................................................................................479 14.6 Collapsibility ..............................................................................................................481 14.7 The Odds (Cross-Product) Ratio .............................................................................484 14.8 Normed Fit Index and Residual Analysis .............................................................485 14.9 Residual Analysis ......................................................................................................486 14.10 Cross-Validation ........................................................................................................486 14.11 Higher Dimensional Tables — Model Selection .....................................................488 14.12 Contrasts for the Log Linear Model .......................................................................493 14.13 Log Linear Analysis for Ordinal Data ...................................................................496 14.14 Sampling and Structural (Fixed) Zeros .................................................................496 14.15 Summary ....................................................................................................................496 14.16 Exercises .....................................................................................................................497 Appendix 14.1: Log Linear Analysis Using Windows for Survey Data .......................501 Contents 15 Hierarchical Linear Modeling .........................................................................................505 Natasha Beretims 15.1 Introduction ...............................................................................................................505 15.2 Problems Using Single-Level Analyses of Multilevel Data ................................506 15.3 Formulation of the Multilevel Model .....................................................................507 15.4 Two-Level Model — General Formulation ..............................................................507 15.5 HLM6 Software .........................................................................................................510 15.6 Two-Level Example — Student and Classroom Data ............................................511 15.7 HLM Software Output .............................................................................................518 15.8 Adding Level-One Predictors to the HLM ............................................................520 15.9 Adding a Second Level-One Predictor to the Level-One Equation ...................525 15.10 Addition of a Level-Two Predictor to a Two-Level HLM ....................................527 15.11 Evaluating the Efficacy of a Treatment ..................................................................529 15.12 Summary ....................................................................................................................535 16 Structural Equation Modeling .........................................................................................537 Leandre R. Fabrigar and Duane T. Wegener 16.1 Introduction ...............................................................................................................537 16.2 Introductory Concepts .............................................................................................537 16.3 The Mathematical Representation of Structural Equation Models ...................540 16.4 Model Specification ...................................................................................................544 16.5 Model Identification ..................................................................................................544 16.6 Specifying Alternative Models ...............................................................................547 16.7 Specifying Multi-Sample Models ...........................................................................553 16.8 Specifying Models in LISREL .................................................................................554 16.9 Specifying Models in EQS .......................................................................................560 16.10 Model Fitting .............................................................................................................562 16.11 Model Evaluation and Modification .......................................................................566 16.12 Model Parsimony ......................................................................................................572 16.13 Model Modification ..................................................................................................572 16.14 LISREL Example of Model Evaluation ...................................................................573 16.15 EQS Example of Model Evaluation .........................................................................576 16.16 Comparisons with Alternative Models in Model Evaluation .............................577 16.17 Summary ....................................................................................................................581 References ...................................................................................................................................583 Appendix A: Statistical Tables ................................................................................................597 Appendix B: Obtaining Nonorthogonal Contrasts in Repeated Measures Designs .....617 Answers .......................................................................................................................................625 Index... ..........................................................................................................................................641
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spellingShingle	Stevens, James Applied multivariate statistics for the social sciences Sozialwissenschaften Multivariate analysis Social sciences Statistical methods Multivariate Analyse (DE-588)4040708-1 gnd Sozialwissenschaften (DE-588)4055916-6 gnd
subject_GND	(DE-588)4040708-1 (DE-588)4055916-6
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 P. Stevens
title_fullStr	Applied multivariate statistics for the social sciences James P. Stevens
title_full_unstemmed	Applied multivariate statistics for the social sciences James P. Stevens
title_short	Applied multivariate statistics for the social sciences
title_sort	applied multivariate statistics for the social sciences
topic	Sozialwissenschaften Multivariate analysis Social sciences Statistical methods Multivariate Analyse (DE-588)4040708-1 gnd Sozialwissenschaften (DE-588)4055916-6 gnd
topic_facet	Sozialwissenschaften Multivariate analysis Social sciences Statistical methods Multivariate Analyse
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017122963&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT stevensjames appliedmultivariatestatisticsforthesocialsciences

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Signatur:	2000 QH 234 S844(5)
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