Preface | Composite-based structural equation modeling | What is structural equation modeling (SEM) | The classical latent variable or common factor model | The composite model | What is composite-based SEM? | Using cSEM | The cSEM-Workflow | Prepare the data | Specify a model | Linear models | Nonlinear models | Hierarchical (second order) models | Estimate using csem() | Inference | Apply postestimation functions | The test_* family of postestimation functions | The do_* family of postestimation functions | Principles underlying cSEM | Model vs. Estimation | Composites in a composite model vs. composites in a common factor model and disattenuation | The role of the weighting scheme and partial least squares (PLS) | Literature
Package: cSEM 0.6.1.9000
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.).
Authors:
cSEM_0.6.1.9000.tar.gz
cSEM_0.6.1.9000.zip(r-4.7)cSEM_0.6.1.9000.zip(r-4.6)cSEM_0.6.1.9000.zip(r-4.5)
cSEM_0.6.1.9000.tgz(r-4.6-any)cSEM_0.6.1.9000.tgz(r-4.5-any)
cSEM_0.6.1.9000.tar.gz(r-4.7-any)cSEM_0.6.1.9000.tar.gz(r-4.6-any)
cSEM_0.6.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
cSEM/json (API)
| # Install 'cSEM' in R: |
| install.packages('cSEM', repos = c('https://floschuberth.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/floschuberth/csem/issues
Pkgdown/docs site:https://floschuberth.github.io
Datasets:
- Anime - Data: Anime
- Benitezetal2020 - Data: Benitezetal2020
- BergamiBagozzi2000 - Data: BergamiBagozzi2000
- corp_rep_data - Data: corp_rep_data
- dgp_2ndorder_cf_of_c - Data: Second order common factor of composites
- ITFlex - Data: ITFlex
- LancelotMiltgenetal2016 - Data: LancelotMiltgenetal2016
- LeDang2022 - Data: LeDang2022
- PoliticalDemocracy - Data: political democracy
- Russett - Data: Russett
- satisfaction - Data: satisfaction
- satisfaction_gender - Data: satisfaction including gender
- Sigma_Summers_composites - Data: Summers
- SQ - Data: SQ
- Switching - Data: Switching
- threecommonfactors - Data: threecommonfactors
- Yooetal2000 - Data: Yooetal2000
Last updated from:36b5bd13bf. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 483 | ||
| source / vignettes | OK | 335 | ||
| linux-release-x86_64 | NOTE | 458 | ||
| macos-release-arm64 | NOTE | 236 | ||
| macos-oldrel-arm64 | NOTE | 260 | ||
| windows-devel | NOTE | 445 | ||
| windows-release | NOTE | 471 | ||
| windows-oldrel | NOTE | 390 | ||
| wasm-release | OK | 144 |
Exports:args_defaultassesscalculateAVEcalculateCFIcalculateChiSquarecalculateChiSquareDfcalculateCNcalculateDfcalculateDGcalculateDLcalculateDMLcalculatef2calculateFLCriterioncalculateGFIcalculateGoFcalculateHTMTcalculateIFIcalculateModelSelectionCriteriacalculateNFIcalculateNNFIcalculateRelativeGoFcalculateRhoCcalculateRhoTcalculateRMSEAcalculateRMSThetacalculateSRMRcalculateVIFModeBcsemdoIPMAdoModelSearchdoNonlinearEffectsAnalysisdoRedundancyAnalysisexportToExcelfitgetConstructScoresinferparseModelpredictresamplecSEMResultsresampleDatasavePlotsummarizetestCVPATtestHausmantestMGDtestMICOMtestOMFverify
Dependencies:abindadmiscalabamaclicodetoolscombinatcpp11crayoncubaturedigestdplyrexpmfarverfuturefuture.applygenericsggplot2globalsgluegmpGPArotationgtableisobandlabelinglatticelavaanlifecyclelistenvmagrittrMASSMatrixmatrixcalcmatrixStatsmnormtmpolymultipolmvtnormnleqslvnlmenumDerivorthopolynomparallellypartitionspbivnormpillarpkgconfigplyrpolycorpolynomprogressrpsychpurrrqrngquadprogR6rbibutilsRColorBrewerRcppRcppArmadilloRdpackrlangS7scalessetsspacefillrstringistringrsymmomentstibbletidyrtidyselectTruncatedNormalutf8vctrsviridisLitewithr
Introduction to cSEM
Last update: 2026-01-22
Started: 2019-04-23
Notation
The structural model | The reflective measurement model | Notation table
Last update: 2026-01-22
Started: 2019-05-14
Terminology
Common factor | Composite | Composite-based methods | Composite-based SEM | Concept | Construct | Covariance-based SEM | Factor-based methods | Indicator | Latent variable | Measurement model | Model | Test score | True score | Proxy | Saturated and non-saturated models | Stand-in | Structural Equation Modeling (SEM) | Variance-based methods | Literature
Last update: 2026-01-22
Started: 2019-05-14
Postestimation: Assessing a model
Introduction | Syntax & Options | Details | Composite models vs. common factor models | Methods & Formulae | Average Variance Extracted (AVE) | Definition | Formulae | Implementation | See also | Degrees of freedom | Notes | See also: | Fit Indices | The $\chi^2$-statistic | The $\chi^2/\text{df}$-ratio | The goodness-of-fit index (GFI) | The standardized root mean square residual (SRMR) | The root mean square error of approximation (RMSEA) | The normed and non-normed fit index (NFI and NNFI) | The comparative fit index (CFI) | The incremental fit index (IFI) | The root mean square outer residual covariance | Reliability | A note on the terminology | Congeneric reliability $\rho_{C;\text{weighted}}$ Dijkstra-Henseler's $\rho_A$weighted | Closed-form confidence interval | The Goodness of Fit (GoF) | The Heterotrait-Monotrait-Ratio of Correlations (HTMT) | Literature
Last update: 2026-01-22
Started: 2019-04-23
