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Table of Contents
Part I Concepts and Tools
1 Introduction 3
The Book's Website 3
Pedagogical Approach 4
Getting Ready to Learn about SEM 5
Characteristics of SEM 7
Widespread Enthusiasm, but with a Cautionary Tale 13
Family History and a Reminder about Context 15
Extended Latent Variable Families 16
Plan of the Book 17
Summary 18
2 Fundamental Concepts 19
Multiple Regression 19
Partial Correlation and Part Correlation 28
Other Bivariate Correlations 31
Logistic Regression 32
Statistical Tests 33
Bootstrapping 42
Summary 43
Recommended Readings 44
Exercises 45
3 Data Preparation 46
Forms of Input Data 46
Positive Definiteness 49
Data Screening 51
Selecting Good Measures and Reporting about Them 68
Summary 72
Recommended Readings 72
Exercises 73
4 Computer Tools 75
Ease of Use, Not Suspension of Judgment 75
Human-Computer Interaction 77
Core SEM Programs and Book Website Resources 77
Other Computer Tools 86
Summary 87
Recommended Readings 87
Part II Core Techniques
5 Specification 91
Steps of SEM 91
Model Diagram Symbols 95
Specification Concepts 96
Path Analysis Models 103
CFA Models 112
Structural Regression Models 118
Exploratory SEM 121
Summary 121
Recommended Readings 122
Exercises 122
6 Identification 124
General Requirements 124
Unique Estimates 130
Rule for Recursive Structural Models 132
Rules for Standard CFA Models 137
Rules for Nonstandard CFA Models 138
Rules for SR Models 144
A Healthy Perspective on Identification 146
Empirical Underidentification 146
Managing Identification Problems 147
Summary 148
Recommended Readings 149
Exercises 149
Appendix 6.A. Evaluation of the Rank Condition 151
7 Estimation 154
Maximum Likelihood Estimation 154
Detailed Example 160
Brief Example with a Start Value Problem 172
Fitting Models to Correlation Matrices 175
Alternative Estimators 176
A Healthy Perspective on Estimation 182
Summary 182
Recommended Readings 183
Exercises 183
Appendix 7.A Start Value Suggestions for Structural Models 185
Appendix 7.B Effect Decomposition in Nonrecursive Models and the Equilibrium Assumption 186
Appendix 7.C Corrected Proportions of Explained Variance for Nonrecursive Models 187
8 Hypothesis Testing 189
Eyes on the Prize 189
State of Practice, State of Mind 190
A Healthy Perspective on Fit Statistics 191
Types of Fit Statistics and "Golden Rules" 193
Model Chi-Square 199
Approximate Fit Indexes 204
Visual Summaries of Fit 209
Recommended Approach to Model Fit Evaluation 209
Detailed Example 210
Testing Hierarchical Models 214
Comparing Nonhierarchical Models 219
Power Analysis 222
Equivalent and Near-Equivalent Models 225
Summary 228
Recommended Readings 228
Exercises 229
9 Measurement Models and Confirmatory Factor Analysis 230
Naming and Reification Fallacies 230
Estimation of CFA Models 231
Detailed Example 233
Respecification of Measurement Models 240
Special Topics and Tests 241
Items as Indicators and Other Methods for Analyzing Items 244
Estimated Factor Scores 245
Equivalent CFA Models 245
Hierarchical CFA Models 248
Models for Multitrait-Multimethod Data 250
Measurement Invariance and Multiple-Sample CFA 251
Summary 261
Recommended Readings 262
Exercises 262
Appendix 9.A Start Value Suggestions for Measurement Models 263
Appendix 9.B Constraint Interaction in Measurement Models 264
10 Structural Regression Models 265
Analyzing SR Models 265
Estimation of SR Models 269
Detailed Example 270
Equivalent SR Models 276
Single Indicators in Partially Latent SR Models 276
Cause Indicators and Formative Measurement 280
Invariance Testing of SR Models 288
Reporting Results of SEM Analyses 289
Summary 293
Recommended Readings 293
Exercises 294
Appendix 10.A Constraint Interaction in SR Models 295
Part III Advanced Techniques, Avoiding Mistakes
11 Mean Structures and Latent Growth Models 299
Logic of Mean Structures 299
Identification of Mean Structures 303
Estimation of Mean Structures 304
Latent Growth Models 304
Structured Means in Measurement Models 316
MIMIC Models as an Alternative to Multiple-Sample Analysis 322
Summary 325
Recommended Readings 326
12 Interaction Effects and Multilevel SEM 327
Interaction Effects of Observed Variables 327
Interaction Effects in Path Models 331
Mediation and Moderation Together 333
Interactive Effects of Latent Variables 336
Estimation with the Kenny-Judd Method 337
Alternative Estimation Methods 340
Rationale of Multilevel Analysis 343
Basic Multilevel Techniques 345
Convergence of SEM and MLM 348
Multilevel SEM 350
Summary 354
Recommended Readings 354
13 How to Fool Yourself with SEM 356
Tripping at the Starting Line: Specification 356
Improper Care and Feeding: Data 359
Checking Critical Judgment at the Door: Analysis and Respecification 361
The Garden Path: Interpretation 363
Summary 366
Recommended Readings 366
Suggested Answers to Exercises 367
References 387
Author Index 405
Subject Index 411
About the Author 427
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