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Tables of Contents for Latent Variable Models
Chapter/Section Title
Page #
Page Count
Preface
ix
Path models in factor, path, and structural equation analysis
1
34
Path diagrams
2
6
Path analysis
8
8
Factor models
16
7
Structural equations
23
1
Original and standardized variables
24
4
Differences from some related topics
28
2
Notes
30
2
Exercises
32
3
Fitting path models
35
52
Iterative solution of path equations
35
5
Matrix formulation of path models
40
4
Full-fledged model-fitting programs
44
8
Fit functions
52
9
Hierarchical χ2 tests
61
6
Descriptive criteria of model fits
67
3
The power to reject an incorrect model
70
3
Identification
73
2
Missing data
75
3
Correlations versus covariances in model fitting
78
2
Notes
80
4
Exercises
84
3
Fitting path and structural models to data from a single group on a single occasion
87
33
Structural and measurement models
87
5
Confirmatory factor analysis
92
3
Some psychometric applications of path and structural models
95
7
Structural models--controlling extraneous variables
102
4
Models with reciprocal influences and correlated errors
106
5
Nonlinear effects among latent variables
111
5
Notes
116
1
Exercises
117
3
Fitting models involving repeated measures or multiple groups
120
32
Models of events over time
121
9
Models comparing different groups
130
9
Fitting models to means as well as covariances
139
8
The versatility of multiple-group designs
147
1
A concluding comment
148
1
Notes
149
1
Exercises
150
2
Exploratory factor analysis--basics
152
35
Factor extraction
154
1
Estimating communalities
154
3
Determining the number of factors
157
12
Rotation
169
8
An example: Thurstone's box problem
177
4
Factor analysis using packaged programs--SPSS and SAS
181
2
Notes
183
2
Exercises
185
2
Exploratory factor analysis--elaborations
187
26
Rescalings--Alpha and Canonical factors
187
3
Alternative stopping criteria
190
3
Alternative rotation methods
193
3
Estimating factor scores
196
5
Higher order factors
201
5
Nonlinear factor analysis
206
4
Notes
210
1
Exercises
211
2
Issues in the application of latent variable analysis
213
25
Exploratory modification of a model
213
4
Alternative models
217
5
Can path diagrams be constructed automatically?
222
2
Modes of latent variable analysis
224
6
Criticisms of latent variable modeling
230
4
Notes
234
2
Exercises
236
2
Appendices
238
27
A. Simple matrix operations
238
7
B. Derivation of matrix version of path equations
245
2
C. LISREL matrices and examples
247
4
D. Various goodness-of-fit indices
251
7
E. Phantom variables
258
2
F. Data matrix for Thurstone's box problem
260
2
G. Table of Chi Square
262
1
H. Noncentral Chi Square for estimating power
263
1
I. Power of a test of poor fit and sample sizes needed for powers of .80 and .90
264
1
Answers to exercises
265
11
References
276
33
Index
309