Package index • cSEM

All functions

Anime: Data: Anime

Benitezetal2020: Data: Benitezetal2020

BergamiBagozzi2000: Data: BergamiBagozzi2000

ITFlex: Data: ITFlex

LancelotMiltgenetal2016: Data: LancelotMiltgenetal2016

PoliticalDemocracy: Data: political democracy

Russett: Data: Russett

SQ: Data: SQ

Sigma_Summers_composites: Data: Summers

Switching: Data: Switching

Yooetal2000: Data: Yooetal2000

args_default(): Show argument defaults or candidates

assess(): Assess model

calculateAVE(): Average variance extracted (AVE)

calculateDf(): Degrees of freedom

calculateFLCriterion(): Fornell-Larcker criterion

calculateGoF(): Goodness of Fit (GoF)

calculateHTMT(): HTMT

calculateModelSelectionCriteria(): Model selection criteria

calculateRelativeGoF(): Relative Goodness of Fit (relative GoF)

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 Cohen's f^2

csem(): Composite-based SEM

dgp_2ndorder_cf_of_c: Data: Second order common factor of composites

calculateDG() calculateDL() calculateDML(): 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

exportToExcel(): Export to Excel (.xlsx)

fit(): Model-implied indicator or construct variance-covariance matrix

calculateChiSquare() calculateChiSquareDf() calculateCFI() calculateGFI() calculateCN() calculateIFI() calculateNFI() calculateNNFI() calculateRMSEA() calculateRMSTheta() calculateSRMR(): Model fit measures

getConstructScores(): Get construct scores

infer(): Inference

parseModel(): Parse lavaan model

plot(<cSEMIPMA>): cSEMIPMA method for plot()

plot(<cSEMNonlinearEffects>): cSEMNonlinearEffects method for plot()

plot(<cSEMResults_2ndorder>): cSEMResults method for plot() for second-order models.

plot(<cSEMResults_default>): cSEMResults method for plot()

plot(<cSEMResults_multi>): cSEMResults method for plot() for multiple groups.

predict(): Predict indicator scores

calculateRhoC() calculateRhoT(): Reliability

resampleData(): Resample data

resamplecSEMResults(): Resample cSEMResults

satisfaction: Data: satisfaction

satisfaction_gender: Data: satisfaction including gender

savePlot(): savePlot

summarize(): Summarize model

testCVPAT(): Perform a Cross-Validated Predictive Ability Test (CVPAT)

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