Assumptions for Confirmatory Factor Analysis CFA

Confirmatory Factor analysis, CFA, questionnaire, scale, Likert scale, survey, data, factor analysis, EFA, latent factors, underlying structure, variables, data, complex approach, tests, hypothesis, items, associated, specific factors, relationships, observed variables, underlying latent factors, confirm, disconfirm, factor structure, data fit, hypothesized model, impose, number of factors, validate, theoretical models, correlate in model, covary, structural equation modeling, SEM, measurement model, evaluation unobserved variables, measurement, instruments, construct validity, Scale development and refinement, quality assurance, confirmatory analysis, mixed-methods research, clinical assessment and diagnosis, assumptions, multivariate normality, normal distribution, linearity, linear, multicollinearity, outlier, reliability, validity, underlying constructs, sample size, estimates, Independence of observations, model specification, measurement error, normality of residuals, random sample, steps, fit, model, research objective, primary goal, hypothesized factor structure, data preparation, data screening, missing values, multivariate normality, transformations, missing data, imputation, factor loadings, parameter estimation, variances, covariances, fit Indices, Chi-square , X2, omparative Fit Index, CFI, Tucker-Lewis Index, TLI, Root Mean Square Error of Approximation RMSEA,
Standardized Root Mean Square Residual, SRMR, statistical software, R, SPSS, AMOS, output, standard errors, modification indices, CMIN, DF, Browne-Cudeck Criterion, BC, Bentler's Comparative Fit Index, BCFI, Parsimony Comparative Fix Index, PCFI, Goodness of fit index, GFI, Adjusted GFI, AGFI, Normed fit index, NFI, non-normed fit index, NNFI, Akaike Information Criterion, AIC, Bayesian Information Criterion, BIC, Expected Cross-Validation Index, ECVI, minimum fit function chi-square statistic, goodness-of-fit statistic, P-value , significant, H0, HA,NPAR, Number of Parameters for each model, FMIN, Index of Model Fit, LO, Hi, Lower, higher boundaries, 90% CI, Confidence interval, Hoelter index, PCLOSE, P-value, Discrepancy, average difference between, null model, Parsimony-Adjusted Measures, PRATIO, Parsimony Ratio, PNFI, Parsimony Normed Fixed Index, PCFI, Parsimony Comparative Fix Index, degrees of freedom, Interpretation, RMR, Root Mean Square Residual, NFI, Normed Fit Index Delta, RFI, Relative Fit Index NFI, IFI, Incremental Fit Index, BIC, Bayes Information Criterion, CAIC, Consistent Akaike Information Criterion, Expected Cross-Validation Index, ECVI, ECVI, Expected Cross Validation Index, MECVI, BrowneCudeck Criterion, BCC, NCP=Non-Centrality Parameter , Residuals, Model Modification, Iterative Process, iterative process, Refine, re-run, analysis, Interpretation, Modifications, Sample characteristics, measurement error, Analyse, Continuous scale, Nominal, Demographic data, Items, Questions, Response, Ordinal, dichotomous, Outcome, Single item, Multiple items, Dependent variable, Independent variable, IV, Exploratory, Predictor, DV, Duplicate, Incomplete, numerical values, categorical data, Multinominal, Code, Reverse coding, composite, Averages, Sums, Descriptive Analysis, Frequency distribution, Calculate , Summary statistics, measures, Mean, Median, Mode, SD, Range, IQ1, IQ3, Data Visualization, Graphs, charts, Create, Bar charts, Pie charts, Histograms, Stacked charts, Scatter plots, Line charts, Factor Analysis, identify, latent, constructs, explain, correlations, Principal component analysis, reduction, PCA, Exploratory factor analysis, Cluster Analysis, Grouping data, Cross-tabulation, categorical variables, , Correlation analysis, Pearson’s correlation coefficients, Spearman’s correlation coefficients, Regression analysis, Linear regression, Binomial regression, Multinomial regression, Ordinal regression, Comparative Analysis, Ethnicity, Parametric tests, T-tests, ANOVA tests, Mann Whitney U test, Kruskal Walis test, Jonckheere's trend test, 95% CI, P-value, Cronbach’s alpha, Validity, Data reduction statistical technique, highly related, Multivariate statistical techniques, method, Dimensionality, variables reduction, principal components, variance, multi-collinearity, matrix scatterplot, Sampling adequacy, Kaiser-Meyer-Olkin, KMO, Bartlett's test of sphericity, rotation, Oblique, Orthogonal, Determinants, structures, patterns, maximum variance, linear combinations, Varimax, Promax, mathematical, transformation, Types of factor extraction, Principal Factor Analysis, PFA, Principal Axis, Factoring, PAF, unobserved factors, bivariate correlation matrix, communalities, eigenvalue, extract, LISREL, EQS, Mplus, LAVAAN package in R, Python package semopy 2, maximum likelihood statistic