Package: semTools 0.5-8.903

Terrence D. Jorgensen

semTools: Useful Tools for Structural Equation Modeling

Provides miscellaneous tools for structural equation modeling, many of which extend the 'lavaan' package. For example, latent interactions can be estimated using product indicators (Lin et al., 2010, <doi:10.1080/10705511.2010.488999>) and simple effects probed; analytical power analyses can be conducted (Jak et al., 2021, <doi:10.3758/s13428-020-01479-0>); and scale reliability can be estimated based on estimated factor-model parameters.

Authors:Terrence D. Jorgensen [aut, cre], Sunthud Pornprasertmanit [aut], Alexander M. Schoemann [aut], Yves Rosseel [aut], Patrick Miller [ctb], Corbin Quick [ctb], Mauricio Garnier-Villarreal [ctb], James Selig [ctb], Aaron Boulton [ctb], Kristopher Preacher [ctb], Donna Coffman [ctb], Mijke Rhemtulla [ctb], Alexander Robitzsch [ctb], Craig Enders [ctb], Ruben Arslan [ctb], Bell Clinton [ctb], Pavel Panko [ctb], Edgar Merkle [ctb], Steven Chesnut [ctb], Jarrett Byrnes [ctb], Jason D. Rights [ctb], Ylenio Longo [ctb], Maxwell Mansolf [ctb], Mattan S. Ben-Shachar [ctb], Mikko Rönkkö [ctb], Andrew R. Johnson [ctb], Leonard Vanbrabant [ctb]

semTools_0.5-8.903.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
semTools/json (API)

# Install 'semTools' in R:

install.packages('semTools', repos = c('https://simsem.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/simsem/semtools/issues

Datasets:

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
exLong - Simulated Data set to Demonstrate Longitudinal Measurement Invariance
simParcel - Simulated Data set to Demonstrate Random Allocations of Parcels

On CRAN:

14.00 score 85 stars 29 packages 1.7k scripts 25k downloads 155 mentions 71 exports 6 dependencies

Last updated from:a51d39bbd4. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	232
source / vignettes	OK	249
linux-release-x86_64	OK	203
macos-release-arm64	OK	232
macos-oldrel-arm64	OK	210
windows-devel	OK	154
windows-release	OK	210
windows-oldrel	OK	186
wasm-release	OK	142

Exports:auxiliary AVE bsBootMiss cfa.2stage cfa.auxiliary chisqSmallN clipboard combinequark compareFit compRelSEM discriminantValidity efa.ekc epcEquivCheck epcEquivFit findRMSEApower findRMSEApowernested findRMSEAsamplesize findRMSEAsamplesizenested fmi goricaSEM growth.2stage growth.auxiliary hist htmt imposeStart indProd kd kurtosis lavaan.2stage lavaan.auxiliary loadingFromAlpha lrv2ord mardiaKurtosis mardiaSkew maximalRelia measEq.syntax monteCarloCI moreFitIndices mvrnonnorm net nullRMSEA orthogonalize parcelAllocation partialInvariance partialInvarianceCat PAVranking permuteMeasEq plausibleValues plotProbe plotRMSEAdist plotRMSEApower plotRMSEApowernested poolMAlloc probe2WayMC probe2WayRC probe3WayMC probe3WayRC quark reliability reliabilityL2 residualCovariate saveFile sem.2stage sem.auxiliary show singleParamTest skew splitSample SSpower tukeySEM twostage

Dependencies:lavaan MASS mnormt numDeriv pbivnorm quadprog

Partial Invariance

Rendered frompartialInvariance.Rnwusingutils::Sweave

Last update: 2014-10-01
Started: 2014-08-28

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

Package: semTools 0.5-8.903

semTools: Useful Tools for Structural Equation Modeling

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