AVE                     Calculate average variance extracted
BootMiss-class          Class For the Results of Bollen-Stine Bootstrap
                        with Incomplete Data
FitDiff-class           Class For Representing A Template of Model Fit
                        Comparisons
Net-class               Class For the Result of Nesting and Equivalence
                        Testing
PAVranking              Parcel-Allocation Variability in Model Ranking
SSpower                 Power for model parameters
auxiliary               Implement Saturated Correlates with FIML
bsBootMiss              Bollen-Stine Bootstrap with the Existence of
                        Missing Data
chisqSmallN             Small-_N_ correction for chi^2 test statistic
clipboard               Copy or save the result of 'lavaan' or
                        'FitDiff' objects into a clipboard or a file
combinequark            Combine the results from the quark function
compRelSEM              Composite Reliability using SEM
compareFit              Build an object summarizing fit indices across
                        multiple models
dat2way                 Simulated Dataset to Demonstrate Two-way Latent
                        Interaction
dat3way                 Simulated Dataset to Demonstrate Three-way
                        Latent Interaction
datCat                  Simulated Data set to Demonstrate Categorical
                        Measurement Invariance
discriminantValidity    Calculate discriminant validity statistics
efa.ekc                 Empirical Kaiser criterion
epcEquivCheck           EPC Equivalence Feasibility Check for
                        Standardized Parameters
epcEquivFit             EPC Equivalence Fit Evaluation Using
                        Modification Indices
exLong                  Simulated Data set to Demonstrate Longitudinal
                        Measurement Invariance
findRMSEApower          Find the statistical power based on population
                        RMSEA
findRMSEApowernested    Find power given a sample size in nested model
                        comparison
findRMSEAsamplesize     Find the minimum sample size for a given
                        statistical power based on population RMSEA
findRMSEAsamplesizenested
                        Find sample size given a power in nested model
                        comparison
fmi                     Fraction of Missing Information.
goricaSEM               Wrapper for 'goric.lavaan()' from the
                        'restriktor' package
htmt                    Assessing Discriminant Validity using
                        Heterotrait-Monotrait Ratio
imposeStart             Specify starting values from a lavaan output
indProd                 Make products of indicators using no centering,
                        mean centering, double-mean centering, or
                        residual centering
kd                      Generate data via the Kaiser-Dickman (1962)
                        algorithm.
kurtosis                Finding excessive kurtosis
lavaan2emmeans          'emmeans' Support Functions for 'lavaan' Models
loadingFromAlpha        Find standardized factor loading from
                        coefficient alpha
lrv2ord                 Calculate Population Moments for Ordinal Data
                        Treated as Numeric
mardiaKurtosis          Finding Mardia's multivariate kurtosis
mardiaSkew              Finding Mardia's multivariate skewness
maximalRelia            Calculate maximal reliability
measEq.syntax           Syntax for measurement equivalence
measEq.syntax-class     Class for Representing a
                        Measurement-Equivalence Model
monteCarloCI            Monte Carlo Confidence Intervals to Test
                        Functions of Parameter Estimates
moreFitIndices          Calculate more fit indices
mvrnonnorm              Generate Non-normal Data using Vale and
                        Maurelli (1983) method
net                     Nesting and Equivalence Testing
nullRMSEA               Calculate the RMSEA of the null model
parcelAllocation        Random Allocation of Items to Parcels in a
                        Structural Equation Model
partialInvariance       Partial Measurement Invariance Testing Across
                        Groups
permuteMeasEq           Permutation Randomization Tests of Measurement
                        Equivalence and Differential Item Functioning
                        (DIF)
permuteMeasEq-class     Class for the Results of Permutation
                        Randomization Tests of Measurement Equivalence
                        and DIF
plausibleValues         Plausible-Values Imputation of Factor Scores
                        Estimated from a lavaan Model
plotProbe               Plot a latent interaction
plotRMSEAdist           Plot the sampling distributions of RMSEA
plotRMSEApower          Plot power curves for RMSEA
plotRMSEApowernested    Plot power of nested model RMSEA
poolMAlloc              Combine sampling variability with
                        parcel-allocation variability by pooling
                        results across M parcel-allocations
probe2WayMC             Probing two-way interaction on the no-centered
                        or mean-centered latent interaction
probe2WayRC             Probing two-way interaction on the
                        residual-centered latent interaction
probe3WayMC             Probing three-way interaction on the
                        no-centered or mean-centered latent interaction
probe3WayRC             Probing three-way interaction on the
                        residual-centered latent interaction
quark                   Quark
residualCovariate       Residual-center all target indicators by
                        covariates
semTools                semTools: Useful Tools for Structural Equation
                        Modeling
simParcel               Simulated Data set to Demonstrate Random
                        Allocations of Parcels
singleParamTest         Single Parameter Test Divided from Nested Model
                        Comparison
skew                    Finding skewness
splitSample             Randomly Split a Data Set into Halves
tukeySEM                Tukey's WSD post-hoc test of means for unequal
                        variance and sample size
twostage                Fit a lavaan model using 2-Stage Maximum
                        Likelihood (TSML) estimation for missing data.
twostage-class          Class for the Results of 2-Stage Maximum
                        Likelihood (TSML) Estimation for Missing Data
