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analysis", "topics": [ "doIPMA" ] }, { "page": "doModelSearch", "title": "Automated model specification search", "topics": [ "doModelSearch" ] }, { "page": "doNonlinearEffectsAnalysis", "title": "Do a nonlinear effects analysis", "topics": [ "doNonlinearEffectsAnalysis" ] }, { "page": "doRedundancyAnalysis", "title": "Do a redundancy analysis", "topics": [ "doRedundancyAnalysis" ] }, { "page": "exportToExcel", "title": "Export to Excel (.xlsx)", "topics": [ "exportToExcel" ] }, { "page": "fit", "title": "Model-implied indicator or construct variance-covariance matrix", "topics": [ "fit" ] }, { "page": "fit_measures", "title": "Model fit measures", "topics": [ "calculateCFI", "calculateChiSquare", "calculateChiSquareDf", "calculateCN", "calculateGFI", "calculateIFI", "calculateNFI", "calculateNNFI", "calculateRMSEA", "calculateRMSTheta", "calculateSRMR", "fit_measures" ] }, { "page": "getConstructScores", "title": "Get construct scores", "topics": [ "getConstructScores" ] }, { "page": "infer", "title": "Inference", "topics": [ "infer" ] }, { "page": "ITFlex", "title": "Data: ITFlex", "topics": [ "ITFlex" ] }, { "page": "LancelotMiltgenetal2016", "title": "Data: LancelotMiltgenetal2016", "topics": [ "LancelotMiltgenetal2016" ] }, { "page": "LeDang2022", "title": "Data: LeDang2022", "topics": [ "LeDang2022" ] }, { "page": "parseModel", "title": "Parse lavaan model", "topics": [ "parseModel" ] }, { "page": "plot.cSEMIPMA", "title": "'cSEMIPMA' method for 'plot()'", "topics": [ "plot.cSEMIPMA" ] }, { "page": "plot.cSEMNonlinearEffects", "title": "'cSEMNonlinearEffects' method for 'plot()'", "topics": [ "plot.cSEMNonlinearEffects" ] }, { "page": "plot.cSEMResults_2ndorder", "title": "'cSEMResults' method for 'plot()' for second-order models.", "topics": [ "plot.cSEMResults_2ndorder" ] }, { "page": "plot.cSEMResults_default", "title": "'cSEMResults' method for 'plot()'", "topics": [ "plot.cSEMResults_default" ] }, { "page": "plot.cSEMResults_multi", "title": "'cSEMResults' method for 'plot()' for multiple groups.", "topics": [ "plot.cSEMResults_multi" ] }, { "page": "PoliticalDemocracy", "title": "Data: political democracy", "topics": [ "PoliticalDemocracy" ] }, { "page": "predict", "title": "Predict indicator scores", "topics": [ "predict" ] }, { "page": "reliability", "title": "Reliability", "topics": [ "calculateRhoC", "calculateRhoT", "reliability" ] }, { "page": "resamplecSEMResults", "title": "Resample cSEMResults", "topics": [ "resamplecSEMResults" ] }, { "page": "resampleData", "title": "Resample data", "topics": [ "resampleData" ] }, { "page": "Russett", "title": "Data: Russett", "topics": [ "Russett" ] }, { "page": "satisfaction", "title": "Data: satisfaction", "topics": [ "satisfaction" ] }, { "page": "satisfaction_gender", "title": "Data: satisfaction including gender", "topics": [ "satisfaction_gender" ] }, { "page": "savePlot", "title": "savePlot", "topics": [ "savePlot" ] }, { "page": "Sigma_Summers_composites", "title": "Data: Summers", "topics": [ "Sigma_Summers_composites" ] }, { "page": "SQ", "title": "Data: SQ", "topics": [ "SQ" ] }, { "page": "summarize", "title": "Summarize model", "topics": [ "summarize" ] }, { "page": "Switching", "title": "Data: Switching", "topics": [ "Switching" ] }, { "page": "testCVPAT", "title": "Perform a Cross-Validated Predictive Ability Test (CVPAT)", "topics": [ "testCVPAT" ] }, { "page": "testHausman", "title": "Regression-based Hausman test", "topics": [ "testHausman" ] }, { "page": "testMGD", "title": "Tests for multi-group comparisons", "topics": [ "testMGD" ] }, { "page": "testMICOM", "title": "Test measurement invariance of composites", "topics": [ "testMICOM" ] }, { "page": "testOMF", "title": "Test for overall model fit", "topics": [ "testOMF" ] }, { "page": "threecommonfactors", "title": "Data: threecommonfactors", "topics": [ "threecommonfactors" ] }, { "page": "verify", "title": "Verify admissibility", "topics": [ "verify" ] }, { "page": "Yooetal2000", "title": "Data: Yooetal2000", "topics": [ "Yooetal2000" ] } ], "_readme": "https://github.com/floschuberth/csem/raw/HEAD/README.md", "_rundeps": [ "abind", "admisc", "alabama", "cli", "codetools", "combinat", "crayon", "cubature", "digest", "expm", "future", "future.apply", "globals", "glue", "GPArotation", "lattice", "lavaan", "lifecycle", "listenv", "magrittr", "MASS", "Matrix", "matrixcalc", "matrixStats", "mnormt", "multipol", "mvtnorm", "nleqslv", "nlme", "numDeriv", "parallelly", "pbivnorm", "polycor", "progressr", "psych", "purrr", "qrng", "quadprog", "rbibutils", "Rcpp", "RcppArmadillo", "Rdpack", "rlang", "spacefillr", "symmoments", "TruncatedNormal", "vctrs" ], "_vignettes": [ { "source": "cSEM.Rmd", "filename": "cSEM.html", "title": "Introduction to cSEM", "author": "Manuel Rademaker", "engine": "knitr::rmarkdown", "headings": [ "Preface", "Composite-based structural equation modeling", "What is structural equation modeling (SEM)", "The classical latent variable or common 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