9781606238776

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 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
	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 Starling 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