Table
of Contents
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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 |
11.8 |
|
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 Nonrecursive 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 |
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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 |
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Hierarchical
CFA Models |
248 |
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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 |
Constraintinteraction 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 |
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Tripping at
the Starting Line: Specification |
356 |
|
Improper
Care and Feeding: Data |
359 |
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Checking
Critical judgment at the Door: Analysis and Respecification |
361 |
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The Garden
Path: Interpretation |
363 |
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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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