Principles and practice of structural equation modeling
Author: Kline, Rex B. Series: Methodology in the social sciences Publisher: Guilford Press 2005.Edition: 2nd ed.Language: EnglishDescription: 366 p. : Graphs ; 24 cm.ISBN: 1572306904Type of document: BookBibliography/Index: Includes bibliographical references and indexItem type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Asia Campus Textbook Collection (PhD) |
H61.25 .K55 2005
(Browse shelf) 900202111 |
Available | 900202111 | |||
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Europe Campus Main Collection |
H61.25 .K55 2005
(Browse shelf) 001176464 |
Available | 001176464 | |||
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Middle East Campus Main Collection |
H61.25 .K55 2005
(Browse shelf) 500004133 |
Available | 500004133 |
Includes bibliographical references and index
Digitized
Principles and Practice of Structural Equation Modeling Contents I. FUNDAMENTAL CONCEPTS 1 · Introduction 1.1 Plan of the Book / 3 1.2 Notation / 6 1.3 Computer Programs for SEM / 6 1.4 Statistical Journeys / 8 1.5 Family Values / 9 1.6 Extended Latent Variable Families / 16 1.7 Family History / 17 1.8 Internet Resources / 18 1.9 Summary / 19 3 2 · Basic Statistical Concepts: I. Correlation and Regression 2.1 Standardized and Unstandardized Variables / 20 2.2 Bivariate Correlation and Regression / 22 2.3 Partial Correlation / 29 2.4 Multiple Correlation and Regression / 30 2.5 Statistical Tests / 40 2.6 Bootstrapping / 42 2.7 Summary / 43 2.8 Recommended Readings / 44 20 3 · Basic Statistical Concepts: Il. Data Preparation and Screening 3.1 Data Preparation / 45 3.2 Data Screening / 48 3.3 Score Reliability and Validity / 58 45 xv xvi Contents 3.4 Summary / 61 3.5 Recommended Readings / 62 4 · Core SEM Techniques and Software 4.1 Steps of SEM / 63 4.2 Path Analysis: A Structural Model of Illness Factors / 66 4.3 Confirmatory Factor Analysis: A Measurement Model of Arousal / 70 4.4 A Structural Regression Model of Family Risk and Child Adjustment / 74 4.5 Extensions / 77 4.6 SEM Computer Programs / 77 4.7 Summary / 89 4.8 Recommended Readings / 90 63 II. CORE TECHNIQUES 5 · Introduction to Path Analysis 5.1 Correlation and Causation / 93 5.2 Specification of Path Models / 95 5.3 Types of Path Models / 102 5.4 Principles of Identification / 105 5.5 Sample Size / 110 5.6 Overview of Estimation Options / 111 5.7 Maximum Likelihood Estimation / 112 5.8 Other Issues / 117 5.9 Summary / 120 5.10 Recommended Readings / 120 APPENDIX 5.A Recommendations for Start Values / 121 APPENDIX 5.B Effect Size Interpretation of Standardized Path Coefficients / 121 93 6. Details of Path Analysis 6.1 Detailed Analysis of a Recursive Model of Illness Factors / 123 6.2 Assessing Model Fit / 133 6.3 Testing Hierarchical Models / 145 6.4 Comparing Nonhierarchical Models / 151 6.5 Equivalent Models / 153 6.6 Power Analysis / 156 6.7 Other Estimation Options / 158 6.8 Summary / 160 6.9 Recommended Readings / 161 123 Contents APPENDIX 6.A Statistical Tests for Indirect Effects in Recursive Path Models / 162 APPENDIX 6.B Amos Basic Syntax / 163 APPENDIX 6.C Estimation of Recursive Path Models with Multiple Regression / 164 xvii 7. Measurement Models and Confirmatory Factor Analysis 7.1 Specification of CFA Models / 165 7.2 Identification of CFA Models / 169 7.3 Naming and Reification Fallacies / 175 7.4 Estimation of CFA Models / 176 7.5 Testing CFA Models / 180 7.6 Equivalent CFA Models / 192 7.7 Analyzing Indicators with Nonnormal Distributions / 194 7.8 Special Types of CFA Models / 198 7.9 Other Issues / 204 7.10 Summary / 206 7.11 Recommended Readings / 206 APPENDIX 7.A Recommendations for Start Values / 207 APPENDIX 7.B CALIS Syntax / 207 165 8 · Models with Structural and Measurement Components 8.1 Characteristics of SR Models / 209 8.2 Analysis of Hybrid Models / 211 8.3 Estimation of SR Models / 219 8.4 A Detailed Example / 221 8.5 Other Issues / 229 8.6 Summary / 232 8.7 Recommended Readings / 233 APPENDIX 8.A SEPATH Syntax / 234 209 III. ADVANCED TECHNIQUES; AVOIDING MISTAKES 9. Nonrecursive Structural Models 9.1 Specification of Nonrecursive Models / 237 9.2 Identification of Nonrecursive Models / 240 9.3 Estimation of Nonrecursive Models / 249 9.4 Examples I 254 9.5 Summary I 260 9.6 Recommended Readings I 261 APPENDIX 9.A EQS Syntax / 262 237 xviii Contents 263 10 · Mean Structures and Latent Growth Models 10.1 10.2 10.3 10.4 10.5 10.6 10.7 10.8 Introduction to Mean Structures / 263 Identification of Mean Structures / 267 Estimation of Mean Structures / 268 Structured Means in Measurement Models / 269 Latent Growth Models / 272 Extensions / 285 Summary / 287 Recommended Readings / 287 APPENDIX 10.A Mplus Syntax / 288 11 · Multiple-Sample SEM 11.1 11.2 11.3 11.4 11.5 Rationale of Multiple-Sample SEM / 289 Multiple-Sample Path Analysis / 290 Multiple-Sample CFA / 295 Extensions / 306 MIMIC Models as an Alternative to Multiple-Sample Analysis / 307 11.6 Summary / 310 11.7 Recommended Readings / 311 APPENDIX 11.A LISREL SIMPLIS Syntax / 312 289 12 · How to Fool Yourself with SEM 12.1 Tripping at the Starting Line: Specification / 313 12.2 Improper Care and Feeding: Data / 316 12.3 Checking Critical Judgment at the Door: Analysis and Respecification / 318 12.4 The Garden Path: Interpretation / 321 12.5 Summary / 324 12.6 Recommended Readings / 324 313 13 · Other Horizons 13.1 Interaction and Curvilinear Effects / 325 13.2 Multilevel Structural Equation Models / 332 13.3 Summary / 336 13.4 Recommended Readings / 337 325 · References · Author Index · Subject Index 338 352 356
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