Principles and Practice of Structural Equation Modeling, Third Edition

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  • Edition: 3rd
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  • Copyright: 2010-08-04
  • Publisher: The Guilford Press
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Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) in the social sciences. This is an accessible volume which covers introductory techniques, including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods, such as the evaluation of nonlinear effects, the analysis of means in covariance structure models, and latent growth models for longitudinal data. Providing examples from various disciplines to illustrate all aspects of SEM, the author offers clear instructions on the preparation and screening of data, common mistakes to avoid, and features of widely used software programs (Amos, EQS, and LISREL). Readers will acquire the skills necessary to begin to use SEM in their own research and to interpret and critique the use of the method by others.

Author Biography

Rex B. Kline is Professor of Psychology at Concordia University in Montral, Qubec, Canada.

Table of Contents

Concepts and Tools
Introductionp. 3
The Book's Websitep. 3
Pedagogical Approachp. 4
Getting Ready to Learn about SEMp. 5
Characteristics of SEMp. 7
Widespread Enthusiasm, but with a Cautionary Talep. 13
Family History and a Reminder about Contextp. 15
Extended Latent Variable Familiesp. 16
Plan of the Bookp. 17
Summaryp. 18
Fundamental Conceptsp. 19
Multiple Regressionp. 19
Partial Correlation and Part Correlationp. 28
Other Bivariate Correlationsp. 31
Logistic Regressionp. 32
Statistical Testsp. 33
Bootstrappingp. 42
Summaryp. 43
Recommended Readingsp. 44
Exercisesp. 45
Data Preparationp. 46
Forms of Input Datap. 46
Positive Definitenessp. 49
Data Screeningp. 51
Selecting Good Measures and Reporting about Themp. 68
Summaryp. 72
Recommended Readingsp. 72
Exercisesp. 73
Computer Toolsp. 75
Ease of Use, Not Suspension of Judgmentp. 75
Human-Computer Interactionp. 77
Core SEM Programs and Book Website Resourcesp. 77
Other Computer Toolsp. 86
Summaryp. 87
Recommended Readingsp. 87
Core Techniques
Specificationp. 91
Steps of SEMp. 91
Model Diagram Symbolsp. 95
Specification Conceptsp. 96
Path Analysis Modelsp. 103
CFA Modelsp. 112
Structural Regression Modelsp. 118
Exploratory SEMp. 121
Summaryp. 121
Recommended Readingsp. 122
Exercisesp. 122
Identificationp. 124
General Requirementsp. 124
Unique Estimatesp. 130
Rule for Recursive Structural Modelsp. 132
Rules for Standard CFA Modelsp. 137
Rules for Nonstandard CFA Modelsp. 138
Rules for SR Modelsp. 144
A Healthy Perspective on Identificationp. 146
Empirical Underidentificationp. 146
Managing Identification Problemsp. 147
Summaryp. 148
Recommended Readingsp. 149
Exercisesp. 149
Appendix 6.A. Evaluation of the Rank Conditionp. 151
Estimationp. 154
Maximum Likelihood Estimationp. 154
Detailed Examplep. 160
Brief Example with a Start Value Problemp. 172
Fitting Models to Correlation Matricesp. 175
Alternative Estimatorsp. 176
A Healthy Perspective on Estimationp. 182
Summaryp. 182
Recommended Readingsp. 183
Exercisesp. 183
Appendix 7.A Start Value Suggestions for Structural Modelsp. 185
Appendix 7.B Effect Decomposition in Nonrecursive Models and the Equilibrium Assumptionp. 186
Appendix 7.C Corrected Proportions of Explained Variance for Nonrecursive Modelsp. 187
Hypothesis Testingp. 189
Eyes on the Prizep. 189
State of Practice, State of Mindp. 190
A Healthy Perspective on Fit Statisticsp. 191
Types of Fit Statistics and "Golden Rules"p. 193
Model Chi-Squarep. 199
Approximate Fit Indexesp. 204
Visual Summaries of Fitp. 209
Recommended Approach to Model Fit Evaluationp. 209
Detailed Examplep. 210
Testing Hierarchical Modelsp. 214
Comparing Nonhierarchical Modelsp. 219
Power Analysisp. 222
Equivalent and Near-Equivalent Modelsp. 225
Summaryp. 228
Recommended Readingsp. 228
Exercisesp. 229
Measurement Models and Confirmatory Factor Analysisp. 230
Naming and Reification Fallaciesp. 230
Estimation of CFA Modelsp. 231
Detailed Examplep. 233
Respecification of Measurement Modelsp. 240
Special Topics and Testsp. 241
Items as Indicators and Other Methods for Analyzing Itemsp. 244
Estimated Factor Scoresp. 245
Equivalent CFA Modelsp. 245
Hierarchical CFA Modelsp. 248
Models for Multitrait-Multimethod Datap. 250
Measurement Invariance and Multiple-Sample CFAp. 251
Summaryp. 261
Recommended Readingsp. 262
Exercisesp. 262
Appendix 9.A Start Value Suggestions for Measurement Modelsp. 263
Appendix 9.B Constraint Interaction in Measurement Modelsp. 264
Structural Regression Modelsp. 265
Analyzing SR Modelsp. 265
Estimation of SR Modelsp. 269
Detailed Examplep. 270
Equivalent SR Modelsp. 276
Single Indicators in Partially Latent SR Modelsp. 276
Cause Indicators and Formative Measurementp. 280
Invariance Testing of SR Modelsp. 288
Reporting Results of SEM Analysesp. 289
Summaryp. 293
Recommended Readingsp. 293
Exercisesp. 294
Appendix 10.A Constraint Interaction in SR Modelsp. 295
Advanced Techniques, Avoiding Mistakes
Mean Structures and Latent Growth Modelsp. 299
Logic of Mean Structuresp. 299
Identification of Mean Structuresp. 303
Estimation of Mean Structuresp. 304
Latent Growth Modelsp. 304
Structured Means in Measurement Modelsp. 316
MIMIC Models as an Alternative to Multiple-Sample Analysisp. 322
Summaryp. 325
Recommended Readingsp. 326
Interaction Effects and Multilevel SEMp. 327
Interaction Effects of Observed Variablesp. 327
Interaction Effects in Path Modelsp. 331
Mediation and Moderation Togetherp. 333
Interactive Effects of Latent Variablesp. 336
Estimation with the Kenny-Judd Methodp. 337
Alternative Estimation Methodsp. 340
Rationale of Multilevel Analysisp. 343
Basic Multilevel Techniquesp. 345
Convergence of SEM and MLMp. 348
Multilevel SEMp. 350
Summaryp. 354
Recommended Readingsp. 354
How to Fool Yourself with SEMp. 356
Tripping at the Starting Line: Specificationp. 356
Improper Care and Feeding: Datap. 359
Checking Critical Judgment at the Door: Analysis and Respecificationp. 361
The Garden Path: Interpretationp. 363
Summaryp. 366
Recommended Readingsp. 366
Suggested Answers to Exercisesp. 367
Referencesp. 387
Author Indexp. 405
Subject Indexp. 411
About the Authorp. 427
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Excellent guide for beginners! August 9, 2011
It's more complete and includes several detailed examples. Very useful for people interesting in conducting structural equation models. The textbook I ordered was exactly the same as what they had listed. I am very pleased with them and will order other books, if possible, in the future.
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Principles and Practice of Structural Equation Modeling, Third Edition: 4 out of 5 stars based on 1 user reviews.

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