BootMiss-class          Class For the Results of Bollen-Stine Bootstrap
                        with Incomplete Data
EFA-class               Class For Rotated Results from EFA
FitDiff-class           Class For Representing A Template of Model Fit
                        Comparisons
Net-class               Class For the Result of Nesting and Equivalence
                        Testing
SSpower                 Power for model parameters
auxiliary               Analyzing data with full-information maximum
                        likelihood with auxiliary variables
bsBootMiss              Bollen-Stine Bootstrap with the Existence of
                        Missing Data
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
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
efaUnrotate             Analyze Unrotated Exploratory Factor Analysis
                        Model
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
fitMeasuresMx           Find fit measures from an MxModel result
fmi                     Fraction of Missing Information.
impliedFactorStat       Calculate the model-implied factor means and
                        covariance matrix.
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
lavaanStar-class        Class For Representing A (Fitted) Latent
                        Variable Model with Additional Elements
lisrel2lavaan           Latent variable modeling in 'lavaan' using
                        LISREL syntax
loadingFromAlpha        Find standardized factor loading from
                        coefficient alpha
longInvariance          Measurement Invariance Tests Within Person
mardiaKurtosis          Finding Mardia's multivariate kurtosis
mardiaSkew              Finding Mardia's multivariate skewness
maximalRelia            Calculate maximal reliability
measurementInvariance   Measurement Invariance Tests
measurementInvarianceCat
                        Measurement Invariance Tests for Categorical
                        Items
miPowerFit              Modification indices and their power approach
                        for model fit evaluation
monteCarloMed           Monte Carlo Confidence Intervals to Test
                        Complex Indirect Effects
moreFitIndices          Calculate more fit indices
mvrnonnorm              Generate Non-normal Data using Vale and
                        Maurelli (1983) method
net                     Nesting and Equivalence Testing
nullMx                  Analyzing data using a null model
nullRMSEA               Calculate the RMSEA of the null model
orthRotate              Implement orthogonal or oblique rotation
parcelAllocation        Random Allocation of Items to Parcels in a
                        Structural Equation Model
partialInvariance       Partial Measurement Invariance Testing Across
                        Groups
plotProbe               Plot the graphs for probing latent interaction
plotRMSEAdist           Plot the sampling distributions of RMSEA
plotRMSEApower          Plot power curves for RMSEA
plotRMSEApowernested    Plot power of nested model RMSEA
probe2WayMC             Probing two-way interaction on the
                        residual-centered latent interaction
probe2WayRC             Probing two-way interaction on the
                        residual-centered latent interaction
probe3WayMC             Probing two-way interaction on the
                        residual-centered latent interaction
probe3WayRC             Probing three-way interaction on the
                        residual-centered latent interaction
quark                   Quark
reliability             Calculate reliability values of factors
reliabilityL2           Calculate the reliability values of a
                        second-order factor
residualCovariate       Residual centered all target indicators by
                        covariates
runMI                   Multiply impute and analyze data using lavaan
saturateMx              Analyzing data using a saturate model
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
standardizeMx           Find standardized estimates for OpenMx output
tukeySEM                Tukey's WSD post-hoc test of means for unequal
                        variance and sample size
wald                    Calculate multivariate Wald statistics
