semTools

Class For the Results of Bollen-Stine Bootstrap with Incomplete Data

Class For Rotated Results from EFA

Class For Representing A Template of Model Fit Comparisons

Class For the Result of Nesting and Equivalence Testing

Parcel-Allocation Variability in Model Ranking

Power for model parameters

Implement Saturated Correlates with FIML

Bollen-Stine Bootstrap with the Existence of Missing Data

Calculate the "D2" statistic

Small-N correction for chi^2 test statistic

Copy or save the result of lavaan or FitDiff objects into a clipboard or a file

Combine the results from the quark function

Build an object summarizing fit indices across multiple models

Simulated Dataset to Demonstrate Two-way Latent Interaction

Simulated Dataset to Demonstrate Three-way Latent Interaction

Simulated Data set to Demonstrate Categorical Measurement Invariance

Calculate discriminant validity statistics

Empirical Kaiser criterion

Analyze Unrotated Exploratory Factor Analysis Model

Simulated Data set to Demonstrate Longitudinal Measurement Invariance

Find the statistical power based on population RMSEA

Find power given a sample size in nested model comparison

Find the minimum sample size for a given statistical power based on population RMSEA

Find sample size given a power in nested model comparison

Fraction of Missing Information.

Assessing Discriminant Validity using Heterotrait-Monotrait Ratio

Specify starting values from a lavaan output

Make products of indicators using no centering, mean centering, double-mean centering, or residual centering

Generate data via the Kaiser-Dickman (1962) algorithm.

Finding excessive kurtosis

Likelihood Ratio Test for Multiple Imputations

Score Test for Multiple Imputations

Wald Test for Multiple Imputations

Class for a lavaan Model Fitted to Multiple Imputations

emmeans Support Functions for lavaan Models

Find standardized factor loading from coefficient alpha

Measurement Invariance Tests Within Person

Finding Mardia's multivariate kurtosis

Finding Mardia's multivariate skewness

Calculate maximal reliability

Syntax for measurement equivalence

Class for Representing a Measurement-Equivalence Model

Measurement Invariance Tests

Measurement Invariance Tests for Categorical Items

Modification indices and their power approach for model fit evaluation

Modification Indices for Multiple Imputations

Monte Carlo Confidence Intervals to Test Complex Indirect Effects

Calculate more fit indices

Generate Non-normal Data using Vale and Maurelli (1983) method

Nesting and Equivalence Testing

Calculate the RMSEA of the null model

Random Allocation of Items to Parcels in a Structural Equation Model

Partial Measurement Invariance Testing Across Groups

Permutation Randomization Tests of Measurement Equivalence and Differential Item Functioning (DIF)

Class for the Results of Permutation Randomization Tests of Measurement Equivalence and DIF

Plausible-Values Imputation of Factor Scores Estimated from a lavaan Model

Plot a latent interaction

Plot the sampling distributions of RMSEA

Plot power curves for RMSEA

Plot power of nested model RMSEA

Pooled estimates and standard errors across M parcel-allocations: Combining sampling variability and parcel-allocation variability.

Probing two-way interaction on the no-centered or mean-centered latent interaction

Probing two-way interaction on the residual-centered latent interaction

Probing three-way interaction on the no-centered or mean-centered latent interaction

Probing three-way interaction on the residual-centered latent interaction

Quark

Calculate reliability values of factors

Calculate the reliability values of a second-order factor

Residual-center all target indicators by covariates

Implement orthogonal or oblique rotation

Fit a lavaan Model to Multiple Imputed Data Sets

semTools: Useful Tools for Structural Equation Modeling

Deprecated functions in package semTools.

Simulated Data set to Demonstrate Random Allocations of Parcels

Single Parameter Test Divided from Nested Model Comparison

Finding skewness

Randomly Split a Data Set into Halves

Tukey's WSD post-hoc test of means for unequal variance and sample size

Fit a lavaan model using 2-Stage Maximum Likelihood (TSML) estimation for missing data.

Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data