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cSEM

Composite-Based Structural Equation Modeling

Estimate, assess, test, and study linear, nonlinear, hierarchical and multigroup structural equation models using composite-based approaches and procedures, including estimation techniques such as partial least squares path modeling (PLS-PM) and its derivatives (PLSc, ordPLSc, robustPLSc), generalized structured component analysis (GSCA), generalized structured component analysis with uniqueness terms (GSCAm), generalized canonical correlation analysis (GCCA), principal component analysis (PCA), factor score regression (FSR) using sum score, regression or bartlett scores (including bias correction using Croon’s approach), as well as several tests and typical postestimation procedures (e.g., verify admissibility of the estimates, assess the model fit, test the model fit etc.).

Functions (103)

Anime

Data: Anime

BergamiBagozzi2000

Data: BergamiBagozzi2000

ITFlex

Data: ITFlex

LancelotMiltgenetal2016

Data: LancelotMiltgenetal2016

PoliticalDemocracy

Data: political democracy

Russett

Data: Russett

Data: SQ

Sigma_Summers_composites

Data: Summers

Switching

Data: Switching

Yooetal2000

Data: Yooetal2000

adjustAlpha

Internal: Multiple testing correction

args_assess_dotdotdot

Complete list of assess()'s ... arguments

args_default

Show argument defaults or candidates

assess

Assess model

cSEM-package

cSEM: A package for composite-based structural equation modeling

calculate2ndStage

Internal: Second/Third stage of the two-stage approach for second order constructs

calculateAVE

Average variance extracted (AVE)

calculateCompositeVCV

Internal: Calculate composite variance-covariance matrix

calculateConstructVCV

Internal: Calculate construct variance-covariance matrix

calculateCorrectionFactors

Internal: Calculate PLSc correction factors

calculateDf

Degrees of freedom

calculateDistance

Internal: Matrix difference

calculateEffects

Internal: Calculate direct, indirect and total effect

calculateFLCriterion

Fornell-Larcker criterion

calculateFR

Internal: ANOVA F-test statistic

calculateGoF

Goodness of Fit (GoF)

calculateHTMT

HTMT

calculateIndicatorCor

Internal: Calculate indicator correlation matrix

calculateInnerWeightsPLS

Internal: Calculate the inner weights for PLS-PM

calculateModelSelectionCriteria

Model selection criteria

calculateOuterWeightsPLS

Internal: Calculate the outer weights for PLS-PM

calculateParameterDifference

Internal: Parameter differences across groups

calculatePr

Internal: Calculation of the CDF used in Henseler et al. (2009)

calculateReliabilities

Internal: Calculate Reliabilities

calculateVIFModeB

Calculate variance inflation factors (VIF) for weights obtained by PLS Mode B

calculateWeightsGSCA

Calculate composite weights using GSCA

calculateWeightsGSCAm

Calculate weights using GSCAm

calculateWeightsKettenring

Calculate composite weights using GCCA

calculateWeightsPCA

Calculate composite weights using principal component analysis (PCA)

calculateWeightsPLS

Calculate composite weights using PLS-PM

calculateWeightsUnit

Calculate composite weights using unit weights

calculatef2

Calculate Cohens f^2

checkConvergence

Internal: Check convergence

classifyConstructs

Internal: Classify structural model terms by type

convertModel

Internal: Convert second order cSEMModel

csem

Composite-based SEM

csem_arguments

cSEMArguments

csem_model

cSEMModel

csem_results

cSEMResults

csem_summary

cSEMSummarize

csem_test

cSEMTest

dgp_2ndorder_cf_of_c

Data: Second order common factor of composites

distance_measures

Calculate difference between S and Sigma_hat

doIPMA

Do an importance-performance matrix analysis

doNonlinearEffectsAnalysis

Do a nonlinear effects analysis

doRedundancyAnalysis

Do a redundancy analysis

estimatePath

Internal: Estimate the structural coefficients

exportToExcel

Export to Excel (.xlsx)

fit

Model-implied indicator or construct variance-covariance matrix

fit_measures

Model fit measures

foreman

Internal: Composite-based SEM

getConstructScores

Get construct scores

getParameterNames

Internal: Parameter names

getRelevantParameters

Internal: Extract relevant parameters from several cSEMResults_multi

getValuesFloodlight

Internal: Helper for doNonlinearEffectsAnalysis()

handleArgs

Internal: Handle arguments

infer

Inference

inference_helper

Internal: Helper for infer()

moments

Internal: Calculate consistent moments of a nonlinear model

nonlinear_estimation_utilities

Internal: Utility functions for the estimation of nonlinear models

parseModel

Parse lavaan model

plot.cSEMIPMA

cSEMIPMA method for plot()

plot.cSEMNonlinearEffects

cSEMNonlinearEffects method for plot()

plot.cSEMPredict

cSEMPredict method for plot()

predict

Predict indicator scores

print.cSEMAssess

cSEMAssess method for print()

print.cSEMNonlinearEffects

cSEMNonlinearEffectsAnalysis method for print()

print.cSEMPlotPredict

cSEMPlotPredict method for print()

print.cSEMPredict

cSEMPredict method for print()

print.cSEMResults

cSEMResults method for print()

print.cSEMSummarize

cSEMSummarize method for print()

print.cSEMTestHausman

cSEMTestHausman method for print()

print.cSEMTestMGD

cSEMTestMGD method for print()

print.cSEMTestMICOM

cSEMTestMICOM method for print()

print.cSEMTestOMF

cSEMTestOMF method for print()

print.cSEMVerify

cSEMVerify method for print()

processData

Internal: Process data

reliability

Reliability

resampleData

Resample data

resamplecSEMResults

Resample cSEMResults

satisfaction

Data: satisfaction

satisfaction_gender

Data: satisfaction including gender

scaleWeights

Internal: Scale weights

setDominantIndicator

Internal: Set the dominant indicator

setStartingValues

Internal: Set starting values

structureTestMGDDecisions

Internal: get structured cSEMTestMGD results

summarize

Summarize model

testHausman

Regression-based Hausman test

testMGD

Tests for multi-group comparisons

testMICOM

Test measurement invariance of composites

testOMF

Test for overall model fit

threecommonfactors

Data: threecommonfactors

verify

Verify admissibility

cSEM

Composite-Based Structural Equation Modeling

v0.4.0

GPL-3

Authors

Manuel E. Rademaker [aut, cre] (<https://orcid.org/0000-0002-8902-3561>), Florian Schuberth [aut] (<https://orcid.org/0000-0002-2110-9086>), Tamara Schamberger [ctb] (<https://orcid.org/0000-0002-7845-784X>), Michael Klesel [ctb] (<https://orcid.org/0000-0002-2884-1819>), Theo K. Dijkstra [ctb], Jörg Henseler [ctb] (<https://orcid.org/0000-0002-9736-3048>)

Initial release

2021-04-09

cSEM

Functions (103)

cSEM

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