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 Croonâs 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.).
Version: 0.6.1 Depends: R (≥ 3.5.0) Imports: alabama, cli, crayon, expm (≥ 0.999-5), future.apply, future, lifecycle, lavaan, magrittr, MASS, Matrix, matrixcalc, matrixStats, polycor, progressr, psych, purrr, Rdpack, rlang, stats, symmoments, TruncatedNormal, utils Suggests: DiagrammeR, DiagrammeRsvg, dplyr, tidyr, knitr, nnls, prettydoc, plotly, rsvg, rmarkdown, rootSolve, listviewer, testthat (≥ 3.0.0), ggplot2, openxlsx, graphics, spelling Published: 2025-05-16 DOI: 10.32614/CRAN.package.cSEM Author: Manuel E. Rademaker [aut], Florian Schuberth [aut, cre], Tamara Schamberger [ctb], Michael Klesel [ctb], Huu Phuc Nguyen [ctb], Theo K. Dijkstra [ctb], Jörg Henseler [ctb] Maintainer: Florian Schuberth <f.schuberth at utwente.nl> BugReports: https://github.com/FloSchuberth/cSEM/issues/ License: GPL-3 URL: https://github.com/FloSchuberth/cSEM/, https://floschuberth.github.io/cSEM/ NeedsCompilation: yes Language: en-US Citation: cSEM citation info Materials: README In views: Psychometrics CRAN checks: cSEM results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=cSEM to link to this page.
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