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semTools (version 0.4-12)
Useful Tools for Structural Equation Modeling
Description
Provides useful tools for structural equation modeling packages.
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Install
install.packages('semTools')
Monthly Downloads
12,396
Version
0.4-12
License
GPL (>= 2)
Issues
8
Pull Requests
3
Stars
72
Forks
35
Repository
https://github.com/simsem/semTools/wiki
Maintainer
Sunthud Pornprasertmanit
Last Published
June 10th, 2016
Functions in semTools (0.4-12)
Search functions
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
BootMiss-class
Class For the Results of Bollen-Stine Bootstrap with Incomplete Data
dat3way
Simulated Dataset to Demonstrate Three-way Latent Interaction
bsBootMiss
Bollen-Stine Bootstrap with the Existence of Missing Data
ci.reliability
Confidence Interval for a Reliability Coefficient
boreal
The Boreal Vegetation Dataset
clipboard_saveFile
Copy or save the result of
lavaan
or
FitDiff
objects into a clipboard or a file
auxiliary
Analyzing data with full-information maximum likelihood with auxiliary variables
fitMeasuresMx
Find fit measures from an MxModel result
EFA-class
Class For Rotated Results from EFA
datCat
Simulated Data set to Demonstrate Categorical Measurement Invariance
FitDiff-class
Class For Representing A Template of Model Fit Comparisons
findRMSEAsamplesizenested
Find sample size given a power in nested model comparison
findRMSEApowernested
Find power given a sample size in nested model comparison
findRMSEApower
Find the statistical power based on population RMSEA
efaUnrotate
Analyze Unrotated Exploratory Factor Analysis Model
exLong
Simulated Data set to Demonstrate Longitudinal Measurement Invariance
findRMSEAsamplesize
Find the minimum sample size for a given statistical power based on population RMSEA
imposeStart
Specify starting values from a lavaan output
lisrel2lavaan
Latent variable modeling in
lavaan
using LISREL syntax
indProd
Make products of indicators using no centering, mean centering, double-mean centering, or residual centering
loadingFromAlpha
Find standardized factor loading from coefficient alpha
htmt
Assessing Discriminant Validity using Heterotrait-Monotrait Ratio
fmi
Fraction of Missing Information.
longInvariance
Measurement Invariance Tests Within Person
kd
Generate data via the Kaiser-Dickman (1962) algorithm.
lavaanStar-class
Class For Representing A (Fitted) Latent Variable Model with Additional Elements
measurementInvariance
Measurement Invariance Tests
monteCarloMed
Monte Carlo Confidence Intervals to Test Complex Indirect Effects
net
Nesting and Equivalence Testing
measurementInvarianceCat
Measurement Invariance Tests for Categorical Items
mvrnonnorm
Generate Non-normal Data using Vale and Maurelli (1983) method
miPowerFit
Modification indices and their power approach for model fit evaluation
nullMx
Analyzing data using a null model
Net-class
Class For the Result of Nesting and Equivalence Testing
partialInvariance
Partial Measurement Invariance Testing Across Groups
PAVranking
Parcel-Allocation Variability in Model Ranking
parcelAllocation
Random Allocation of Items to Parcels in a Structural Equation Model
permuteMeasEq-class
Class for the Results of Permutation Randomization Tests of Measurement Equivalence and DIF
residualCovariate
Residual centered all target indicators by covariates
plotRMSEApowernested
Plot power of nested model RMSEA
permuteMeasEq
Permutation Randomization Tests of Measurement Equivalence and Differential Item Functioning (DIF)
poolMAlloc
Pooled estimates and standard errors across M parcel-allocations: Combining sampling variability and parcel-allocation variability.
quark
Quark
plotProbe
Plot the graphs for probing latent interaction
probe3WayRC
Probing three-way interaction on the residual-centered latent interaction
probe2WayRC
Probing two-way interaction on the residual-centered latent interaction
plotRMSEApower
Plot power curves for RMSEA
spatialCorrect
Calculate reliability values of factors
runMI
Multiply impute and analyze data using lavaan
singleParamTest
Single Parameter Test Divided from Nested Model Comparison
rotate
Implement orthogonal or oblique rotation
standardizeMx
Find standardized estimates for OpenMx output
SSpower
Power for model parameters
saturateMx
Analyzing data using a saturate model
simParcel
Simulated Data set to Demonstrate Random Allocations of Parcels