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Structural Equation Modeling: Applications Using Mplus by Xiaoqian Wang, Jichuan Wang

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Index

across-validation index (CVI)

adjusted ADF χ2

adjusted Lo-Mendell-Rubin LR (ALMR LR) test

Akaike's information criterion (AIC)

approximate noncentrality parameter

asymptotically distribution free (ADF) estimation method

attrition

average posterior probability

Bayesian information criterion (BIC)

between subject models

binary indicators

biserial correlation

bootstrap likelihood ratio (BLRT) test

bundling items

categorical latent variable

causal effects invariance

censored data

censoring

centering time score

CFA model

with binary indicators

with categorical indicators

with censored data

with non-normal indicators

change in CFI (ΔCFI)

classification uncertainty

close-fit test

cluster analysis

collinearity

common metric completely standardized solution

communality

comparative fit index (CFI)

conditional CLA model

conditional GMM

conditional independence

conditional item-response probabilities

conditional probabilities

configural invariance

configural measurement invariance

configural model

confirmatory factor analysis (CFA)

congeneric measures

construct reliability

construct validity

correct class membership assignment

correcting for measurement error in a single indicator variable

covariance structure (COVS)

coverage

Cronbach's alpha

cross-sectional hybrid model

curvilinear growth pattern

defining latent classes

delta parameterization

differential item functioning (DIF)

direct effect

distal outcome

distributed parcelling

EFA

effect size

eight parameter matrices

endogenous ...

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