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semTools (version 0.4-11)

Useful Tools for Structural Equation Modeling

Description

Provides useful tools for structural equation modeling packages.

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Version

Install

install.packages('semTools')

Monthly Downloads

12,021

Version

0.4-11

License

GPL (>= 2)

Issues

6

Pull Requests

2

Stars

75

Forks

35

Maintainer

Sunthud Pornprasertmanit

Last Published

March 1st, 2016

Functions in semTools (0.4-11)

impliedFactorStat

Calculate the model-implied factor means and covariance matrix.
auxiliary

Analyzing data with full-information maximum likelihood with auxiliary variables
monteCarloMed

Monte Carlo Confidence Intervals to Test Complex Indirect Effects
probe2WayRC

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

Specify starting values from a lavaan output
exLong

Simulated Data set to Demonstrate Longitudinal Measurement Invariance
mardiaKurtosis

Finding Mardia's multivariate kurtosis
lisrel2lavaan

Latent variable modeling in lavaan using LISREL syntax
bsBootMiss

Bollen-Stine Bootstrap with the Existence of Missing Data
plotRMSEAdist

Plot the sampling distributions of RMSEA
nullRMSEA

Calculate the RMSEA of the null model
ci.reliability

Confidence Interval for a Reliability Coefficient
simParcel

Simulated Data set to Demonstrate Random Allocations of Parcels
EFA-class

Class For Rotated Results from EFA
Net-class

Class For the Result of Nesting and Equivalence Testing
probe3WayRC

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

Multiply impute and analyze data using lavaan
dat3way

Simulated Dataset to Demonstrate Three-way Latent Interaction
loadingFromAlpha

Find standardized factor loading from coefficient alpha
mardiaSkew

Finding Mardia's multivariate skewness
longInvariance

Measurement Invariance Tests Within Person
maximalRelia

Calculate maximal reliability
compareFit

Build an object summarizing fit indices across multiple models
SSpower

Power for model parameters
boreal

The Boreal Vegetation Dataset
probe2WayMC

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

Find fit measures from an MxModel result
measurementInvarianceCat

Measurement Invariance Tests for Categorical Items
combinequark

Combine the results from the quark function
moreFitIndices

Calculate more fit indices
efaUnrotate

Analyze Unrotated Exploratory Factor Analysis Model
findRMSEApower

Find the statistical power based on population RMSEA
findRMSEAsamplesize

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

Measurement Invariance Tests
findRMSEAsamplesizenested

Find sample size given a power in nested model comparison
spatialCorrect

Calculate reliability values of factors
clipboard_saveFile

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

Modification indices and their power approach for model fit evaluation
lavaanStar-class

Class For Representing A (Fitted) Latent Variable Model with Additional Elements
plotProbe

Plot the graphs for probing latent interaction
datCat

Simulated Data set to Demonstrate Categorical Measurement Invariance
quark

Quark
PAVranking

Parcel-Allocation Variability in Model Ranking
fmi

Fraction of Missing Information.
BootMiss-class

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

Analyzing data using a saturate model
probe3WayMC

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

Calculate reliability values of factors
wald

Calculate multivariate Wald statistics
plotRMSEApowernested

Plot power of nested model RMSEA
permuteMeasEq-class

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

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

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

Generate data via the Kaiser-Dickman (1962) algorithm.
reliabilityL2

Calculate the reliability values of a second-order factor
singleParamTest

Single Parameter Test Divided from Nested Model Comparison
dat2way

Simulated Dataset to Demonstrate Two-way Latent Interaction
standardizeMx

Find standardized estimates for OpenMx output
parcelAllocation

Random Allocation of Items to Parcels in a Structural Equation Model
plotRMSEApower

Plot power curves for RMSEA
skew

Finding skewness
residualCovariate

Residual centered all target indicators by covariates
rotate

Implement orthogonal or oblique rotation
FitDiff-class

Class For Representing A Template of Model Fit Comparisons
findRMSEApowernested

Find power given a sample size in nested model comparison
kurtosis

Finding excessive kurtosis
indProd

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

Nesting and Equivalence Testing
nullMx

Analyzing data using a null model
partialInvariance

Partial Measurement Invariance Testing Across Groups