# semTools v0.5-2

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## Useful Tools for Structural Equation Modeling

Provides useful tools for structural equation modeling.

# semTools

Useful tools for structural equation modeling.

This is an R package whose primary purpose is to extend the functionality of the R package lavaan. There are several suites of tools in the package, which correspond to the same theme. To browse these suites, open the help page at the Console:

?semTools::semTools-package


Additional tools are available to do not require users to rely on any R packages for SEM (e.g., lavaan, OpenMx, or sem), as long as their other software provides the information they need. Examples:

• monteCarloMed() to calculate Monte Carlo confidence intervals for functions of parameters, such as indirect effects in mediation models
• calculate.D2() to pool z or chi-squared statistics across multiple imputations of missing data
• indProd() for creating product indicators of latent interactions
• SSpower() provides analytically derived power estimates for SEMs
• tukeySEM() for Tukey's WSD post-hoc test of mean-differences under unequal variance and sample size
• bsBootMiss() to transform incomplete data to be consistent with the null-hypothesized model, appropriate for model-based (a.k.a. "Bollen--Stine") boostrapping

All users of R (or SEM) are invited to submit functions or ideas for functions by contacting the maintainer, Terrence Jorgensen (TJorgensen314 at gmail dot com). Contributors are encouraged to use Roxygen comments to document their contributed code, which is consistent with the rest of semTools. Read the vignette from the roxygen2 package for details:

vignette("rd", package = "roxygen2")


## Functions in semTools

 Name Description EFA-class Class For Rotated Results from EFA SSpower Power for model parameters FitDiff-class Class For Representing A Template of Model Fit Comparisons chisqSmallN k-factor correction for $chi^2$ test statistic BootMiss-class Class For the Results of Bollen-Stine Bootstrap with Incomplete Data Net-class Class For the Result of Nesting and Equivalence Testing calculate.D2 Calculate the "D2" statistic auxiliary Implement Saturated Correlates with FIML PAVranking Parcel-Allocation Variability in Model Ranking bsBootMiss Bollen-Stine Bootstrap with the Existence of Missing Data exLong Simulated Data set to Demonstrate Longitudinal Measurement Invariance efaUnrotate Analyze Unrotated Exploratory Factor Analysis Model imposeStart Specify starting values from a lavaan output efa.ekc Empirical Kaiser criterion htmt Assessing Discriminant Validity using Heterotrait-Monotrait Ratio clipboard Copy or save the result of lavaan or FitDiff objects into a clipboard or a file kurtosis Finding excessive kurtosis lavTestLRT.mi Likelihood Ratio Test for Multiple Imputations datCat Simulated Data set to Demonstrate Categorical Measurement Invariance combinequark Combine the results from the quark function dat3way Simulated Dataset to Demonstrate Three-way Latent Interaction compareFit Build an object summarizing fit indices across multiple models findRMSEAsamplesizenested Find sample size given a power in nested model comparison fmi Fraction of Missing Information. dat2way Simulated Dataset to Demonstrate Two-way Latent Interaction findRMSEApower Find the statistical power based on population RMSEA findRMSEAsamplesize Find the minimum sample size for a given statistical power based on population RMSEA findRMSEApowernested Find power given a sample size in nested model comparison loadingFromAlpha Find standardized factor loading from coefficient alpha lavaan.mi-class Class for a lavaan Model Fitted to Multiple Imputations maximalRelia Calculate maximal reliability mardiaSkew Finding Mardia's multivariate skewness mvrnonnorm Generate Non-normal Data using Vale and Maurelli (1983) method nullRMSEA Calculate the RMSEA of the null model lavTestScore.mi Score Test for Multiple Imputations indProd Make products of indicators using no centering, mean centering, double-mean centering, or residual centering measurementInvariance-deprecated Measurement Invariance Tests kd Generate data via the Kaiser-Dickman (1962) algorithm. lavTestWald.mi Wald Test for Multiple Imputations net Nesting and Equivalence Testing miPowerFit Modification indices and their power approach for model fit evaluation longInvariance-deprecated Measurement Invariance Tests Within Person modindices.mi Modification Indices for Multiple Imputations monteCarloMed Monte Carlo Confidence Intervals to Test Complex Indirect Effects mardiaKurtosis Finding Mardia's multivariate kurtosis moreFitIndices Calculate more fit indices measEq.syntax Syntax for measurement equivalence measEq.syntax-class Class for Representing a Measurement-Equivalence Model plotRMSEApower Plot power curves for RMSEA plotRMSEApowernested Plot power of nested model RMSEA partialInvariance Partial Measurement Invariance Testing Across Groups permuteMeasEq-class Class for the Results of Permutation Randomization Tests of Measurement Equivalence and DIF measurementInvarianceCat-deprecated Measurement Invariance Tests for Categorical Items plotProbe Plot a latent interaction plotRMSEAdist Plot the sampling distributions of RMSEA plausibleValues Plausible-Values Imputation of Factor Scores Estimated from a lavaan Model permuteMeasEq Permutation Randomization Tests of Measurement Equivalence and Differential Item Functioning (DIF) 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 singleParamTest Single Parameter Test Divided from Nested Model Comparison skew Finding skewness orthRotate Implement orthogonal or oblique rotation twostage Fit a lavaan model using 2-Stage Maximum Likelihood (TSML) estimation for missing data. residualCovariate Residual-center all target indicators by covariates twostage-class Class for the Results of 2-Stage Maximum Likelihood (TSML) Estimation for Missing Data poolMAlloc Pooled estimates and standard errors across M parcel-allocations: Combining sampling variability and parcel-allocation variability. reliability Calculate reliability values of factors probe2WayMC Probing two-way interaction on the no-centered or mean-centered latent interaction parcelAllocation Random Allocation of Items to Parcels in a Structural Equation Model semTools-deprecated Deprecated functions in package semTools. runMI Fit a lavaan Model to Multiple Imputed Data Sets probe3WayRC Probing three-way interaction on the residual-centered latent interaction splitSample Randomly Split a Data Set into Halves tukeySEM Tukey's WSD post-hoc test of means for unequal variance and sample size quark Quark reliabilityL2 Calculate the reliability values of a second-order factor semTools semTools: Useful Tools for Structural Equation Modeling simParcel Simulated Data set to Demonstrate Random Allocations of Parcels No Results!