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647
Index
additive constant (intercept), 221
ADF, asymptotically distribution-free, 594
admissibility test in Bayesian estimation, 420
AGFI, adjusted goodness-of-fit index, 614
AIC
Akaike information criterion,
309, 605
Burnham and Anderson’s guidelines for, 326
Akaike weights, 628, 629
interpreting, 328
viewing, 327
alternative to analysis of covariance, 145, 241
Amos Graphics, launching, 9
AmosEngine methods, 57
analysis of covariance, 147
alternative to, 145, 241
comparison of methods, 256
Anderson iris data, 521, 539
assumptions by Amos
about analysis of covariance,
241
about correlations among exogenous variables,
77
about distribution, 35
about missing data, 270
about parameters in the measurement model, 245
about regression, 221
asymptotic, 30
autocorrelation plot, 402, 505
backwards heuristic specification search, 358
baseline model, 625
comparisons to, 608
specifying, 626
Bayes factors, 628, 629
rescaling of, 331
Bayes’ Theorem, 385
Bayesian estimation, 385
of additional estimands, 428
Bayesian imputation, 462
BCC
Browne-Cudeck criterion,
309, 606
Burnham and Anderson’s guidelines for, 326
comparing models using, 326
best-fit graph
for C,
338
for fit measures, 339
point of diminishing returns, 339
BIC
Bayes information criterion,
606
comparing models using, 347
bootstrap, 295–301
ADF, 314
approach to model comparison, 303–310
compare estimation methods, 311–318
failures, 309
GLS, 314
ML, 314
monitoring progress, 297
number of samples, 297, 307
samples, 303
shortcomings, 296
table of diagnostic information, 299
ULS, 314
boundaries. See category boundaries
burn-in samples,
395
CAIC, consistent AIC, 607
calculate
critical ratios,
110
standardized estimates, 33
Caption
pd method for drawing path diagrams,
583