A B C D E F G H I K L M N O P Q R S T V W
| anova-method | Class For Representing A (Fitted) Latent Variable Model with Additional Elements |
| anova-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| auxiliary | Analyzing data with full-information maximum likelihood with auxiliary variables |
| BootMiss-class | Class For the Results of Bollen-Stine Bootstrap with Incomplete Data |
| bsBootMiss | Bollen-Stine Bootstrap with the Existence of Missing Data |
| cfa.2stage | Fit a lavaan model using 2-Stage Maximum Likelihood (TSML) estimation for missing data. |
| cfa.auxiliary | Analyzing data with full-information maximum likelihood with auxiliary variables |
| cfa.mi | Multiply impute and analyze data using lavaan |
| chisqSmallN | _k_-factor correction for chi-squared test statistic |
| clipboard | Copy or save the result of 'lavaan' or 'FitDiff' objects into a clipboard or a file |
| coef-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| 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 |
| EFA-class | Class For Rotated Results from EFA |
| 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 |
| FitDiff-class | Class For Representing A Template of Model Fit Comparisons |
| fitMeasuresMx | Find fit measures from an MxModel result |
| fitted-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| fitted.values-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| fmi | Fraction of Missing Information. |
| funRotate | Implement orthogonal or oblique rotation |
| growth.2stage | Fit a lavaan model using 2-Stage Maximum Likelihood (TSML) estimation for missing data. |
| growth.auxiliary | Analyzing data with full-information maximum likelihood with auxiliary variables |
| growth.mi | Multiply impute and analyze data using lavaan |
| hist-method | Class For the Results of Bollen-Stine Bootstrap with Incomplete Data |
| hist-method | Class for the Results of Permutation Randomization Tests of Measurement Equivalence and DIF |
| 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 |
| inspect-method | Class For Representing A (Fitted) Latent Variable Model with Additional Elements |
| kd | Generate data via the Kaiser-Dickman (1962) algorithm. |
| kurtosis | Finding excessive kurtosis |
| lavaan.2stage | Fit a lavaan model using 2-Stage Maximum Likelihood (TSML) estimation for missing data. |
| lavaan.auxiliary | Analyzing data with full-information maximum likelihood with auxiliary variables |
| lavaan.mi | Multiply impute and analyze data using lavaan |
| 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 |
| 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 |
| Net-class | Class For the Result of Nesting and Equivalence Testing |
| nobs-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| nullMx | Analyzing data using a null model |
| nullRMSEA | Calculate the RMSEA of the null model |
| oblqRotate | Implement orthogonal or oblique rotation |
| orthogonalize | Make products of indicators using no centering, mean centering, double-mean centering, or residual centering |
| 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 |
| partialInvarianceCat | Partial Measurement Invariance Testing Across Groups |
| PAVranking | Parcel-Allocation Variability in Model Ranking |
| 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 |
| 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 |
| poolMAlloc | Pooled estimates and standard errors across M parcel-allocations: Combining sampling variability and parcel-allocation variability. |
| 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 two-way interaction on the no-centered or mean-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 |
| resid-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| residualCovariate | Residual centered all target indicators by covariates |
| residuals-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| runMI | Multiply impute and analyze data using lavaan |
| saturateMx | Analyzing data using a saturate model |
| saveFile | Copy or save the result of 'lavaan' or 'FitDiff' objects into a clipboard or a file |
| sem.2stage | Fit a lavaan model using 2-Stage Maximum Likelihood (TSML) estimation for missing data. |
| sem.auxiliary | Analyzing data with full-information maximum likelihood with auxiliary variables |
| sem.mi | Multiply impute and analyze data using lavaan |
| show-method | Class For the Results of Bollen-Stine Bootstrap with Incomplete Data |
| show-method | Class For Rotated Results from EFA |
| show-method | Class For Representing A Template of Model Fit Comparisons |
| show-method | Class For the Result of Nesting and Equivalence Testing |
| show-method | Class for the Results of Permutation Randomization Tests of Measurement Equivalence and DIF |
| show-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| 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 |
| SSpower | Power for model parameters |
| standardizeMx | Find standardized estimates for OpenMx output |
| summary-method | Class For the Results of Bollen-Stine Bootstrap with Incomplete Data |
| summary-method | Class For Rotated Results from EFA |
| summary-method | Class For Representing A Template of Model Fit Comparisons |
| summary-method | Class For the Result of Nesting and Equivalence Testing |
| summary-method | Class For Representing A (Fitted) Latent Variable Model with Additional Elements |
| summary-method | Class for the Results of Permutation Randomization Tests of Measurement Equivalence and DIF |
| summary-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| 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 |
| vcov-method | Class For Representing A (Fitted) Latent Variable Model with Additional Elements |
| vcov-method | Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data |
| wald | Calculate multivariate Wald statistics |