Concepts and Tools | |

Introduction | p. 3 |

The Book's Website | p. 3 |

Pedagogical Approach | p. 4 |

Getting Ready to Learn about SEM | p. 5 |

Characteristics of SEM | p. 7 |

Widespread Enthusiasm, but with a Cautionary Tale | p. 13 |

Family History and a Reminder about Context | p. 15 |

Extended Latent Variable Families | p. 16 |

Plan of the Book | p. 17 |

Summary | p. 18 |

Fundamental Concepts | p. 19 |

Multiple Regression | p. 19 |

Partial Correlation and Part Correlation | p. 28 |

Other Bivariate Correlations | p. 31 |

Logistic Regression | p. 32 |

Statistical Tests | p. 33 |

Bootstrapping | p. 42 |

Summary | p. 43 |

Recommended Readings | p. 44 |

Exercises | p. 45 |

Data Preparation | p. 46 |

Forms of Input Data | p. 46 |

Positive Definiteness | p. 49 |

Data Screening | p. 51 |

Selecting Good Measures and Reporting about Them | p. 68 |

Summary | p. 72 |

Recommended Readings | p. 72 |

Exercises | p. 73 |

Computer Tools | p. 75 |

Ease of Use, Not Suspension of Judgment | p. 75 |

Human-Computer Interaction | p. 77 |

Core SEM Programs and Book Website Resources | p. 77 |

Other Computer Tools | p. 86 |

Summary | p. 87 |

Recommended Readings | p. 87 |

Core Techniques | |

Specification | p. 91 |

Steps of SEM | p. 91 |

Model Diagram Symbols | p. 95 |

Specification Concepts | p. 96 |

Path Analysis Models | p. 103 |

CFA Models | p. 112 |

Structural Regression Models | p. 118 |

Exploratory SEM | p. 121 |

Summary | p. 121 |

Recommended Readings | p. 122 |

Exercises | p. 122 |

Identification | p. 124 |

General Requirements | p. 124 |

Unique Estimates | p. 130 |

Rule for Recursive Structural Models | p. 132 |

Rules for Standard CFA Models | p. 137 |

Rules for Nonstandard CFA Models | p. 138 |

Rules for SR Models | p. 144 |

A Healthy Perspective on Identification | p. 146 |

Empirical Underidentification | p. 146 |

Managing Identification Problems | p. 147 |

Summary | p. 148 |

Recommended Readings | p. 149 |

Exercises | p. 149 |

Appendix 6.A. Evaluation of the Rank Condition | p. 151 |

Estimation | p. 154 |

Maximum Likelihood Estimation | p. 154 |

Detailed Example | p. 160 |

Brief Example with a Start Value Problem | p. 172 |

Fitting Models to Correlation Matrices | p. 175 |

Alternative Estimators | p. 176 |

A Healthy Perspective on Estimation | p. 182 |

Summary | p. 182 |

Recommended Readings | p. 183 |

Exercises | p. 183 |

Appendix 7.A Start Value Suggestions for Structural Models | p. 185 |

Appendix 7.B Effect Decomposition in Nonrecursive Models and the Equilibrium Assumption | p. 186 |

Appendix 7.C Corrected Proportions of Explained Variance for Nonrecursive Models | p. 187 |

Hypothesis Testing | p. 189 |

Eyes on the Prize | p. 189 |

State of Practice, State of Mind | p. 190 |

A Healthy Perspective on Fit Statistics | p. 191 |

Types of Fit Statistics and "Golden Rules" | p. 193 |

Model Chi-Square | p. 199 |

Approximate Fit Indexes | p. 204 |

Visual Summaries of Fit | p. 209 |

Recommended Approach to Model Fit Evaluation | p. 209 |

Detailed Example | p. 210 |

Testing Hierarchical Models | p. 214 |

Comparing Nonhierarchical Models | p. 219 |

Power Analysis | p. 222 |

Equivalent and Near-Equivalent Models | p. 225 |

Summary | p. 228 |

Recommended Readings | p. 228 |

Exercises | p. 229 |

Measurement Models and Confirmatory Factor Analysis | p. 230 |

Naming and Reification Fallacies | p. 230 |

Estimation of CFA Models | p. 231 |

Detailed Example | p. 233 |

Respecification of Measurement Models | p. 240 |

Special Topics and Tests | p. 241 |

Items as Indicators and Other Methods for Analyzing Items | p. 244 |

Estimated Factor Scores | p. 245 |

Equivalent CFA Models | p. 245 |

Hierarchical CFA Models | p. 248 |

Models for Multitrait-Multimethod Data | p. 250 |

Measurement Invariance and Multiple-Sample CFA | p. 251 |

Summary | p. 261 |

Recommended Readings | p. 262 |

Exercises | p. 262 |

Appendix 9.A Start Value Suggestions for Measurement Models | p. 263 |

Appendix 9.B Constraint Interaction in Measurement Models | p. 264 |

Structural Regression Models | p. 265 |

Analyzing SR Models | p. 265 |

Estimation of SR Models | p. 269 |

Detailed Example | p. 270 |

Equivalent SR Models | p. 276 |

Single Indicators in Partially Latent SR Models | p. 276 |

Cause Indicators and Formative Measurement | p. 280 |

Invariance Testing of SR Models | p. 288 |

Reporting Results of SEM Analyses | p. 289 |

Summary | p. 293 |

Recommended Readings | p. 293 |

Exercises | p. 294 |

Appendix 10.A Constraint Interaction in SR Models | p. 295 |

Advanced Techniques, Avoiding Mistakes | |

Mean Structures and Latent Growth Models | p. 299 |

Logic of Mean Structures | p. 299 |

Identification of Mean Structures | p. 303 |

Estimation of Mean Structures | p. 304 |

Latent Growth Models | p. 304 |

Structured Means in Measurement Models | p. 316 |

MIMIC Models as an Alternative to Multiple-Sample Analysis | p. 322 |

Summary | p. 325 |

Recommended Readings | p. 326 |

Interaction Effects and Multilevel SEM | p. 327 |

Interaction Effects of Observed Variables | p. 327 |

Interaction Effects in Path Models | p. 331 |

Mediation and Moderation Together | p. 333 |

Interactive Effects of Latent Variables | p. 336 |

Estimation with the Kenny-Judd Method | p. 337 |

Alternative Estimation Methods | p. 340 |

Rationale of Multilevel Analysis | p. 343 |

Basic Multilevel Techniques | p. 345 |

Convergence of SEM and MLM | p. 348 |

Multilevel SEM | p. 350 |

Summary | p. 354 |

Recommended Readings | p. 354 |

How to Fool Yourself with SEM | p. 356 |

Tripping at the Starting Line: Specification | p. 356 |

Improper Care and Feeding: Data | p. 359 |

Checking Critical Judgment at the Door: Analysis and Respecification | p. 361 |

The Garden Path: Interpretation | p. 363 |

Summary | p. 366 |

Recommended Readings | p. 366 |

Suggested Answers to Exercises | p. 367 |

References | p. 387 |

Author Index | p. 405 |

Subject Index | p. 411 |

About the Author | p. 427 |

Table of Contents provided by Ingram. All Rights Reserved. |