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semTests: Robust Test Statistics for Structural Equation Models

Computes robust p-values for overall fit and nested comparisons of structural equation models fitted with 'lavaan'. Implements penalized eigenvalue block averaging and penalized regression (Foldnes, Moss, Grønneberg, 2025) <doi:10.1080/10705511.2024.2372028>, including their extension to nested models (Foldnes, Grønneberg, Moss, 2026) <doi:10.3758/s13428-026-02968-4>, alongside familiar corrections such as Satorra-Bentler. Supported settings include complete-data ML, GLS, and ULS, categorical DWLS and ULS, and full-information maximum likelihood with one or several groups.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: lavaan (≥ 0.7-2), methods
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2026-07-19
DOI: 10.32614/CRAN.package.semTests
Author: Jonas Moss ORCID iD [aut, cre], Njål Foldnes ORCID iD [ctb], Steffen Grønneberg ORCID iD [ctb]
Maintainer: Jonas Moss <jonas.moss.statistics at gmail.com>
License: GPL (≥ 3)
URL: https://github.com/JonasMoss/semTests
NeedsCompilation: no
Citation: semTests citation info
Materials: README, NEWS
CRAN checks: semTests results

Documentation:

Reference manual: semTests.html , semTests.pdf
Vignettes: Categorical and mixed-indicator models (source, R code)
Complete continuous-data models (source, R code)
FIML models and information conventions (source, R code)
Latent growth models with missing data (source, R code)
Measurement invariance with ordinal indicators (source, R code)
Robust test statistics with semTests (source, R code)

Downloads:

Package source: semTests_1.0.0.tar.gz
Windows binaries: r-devel: not available, r-release: semTests_1.0.0.zip, r-oldrel: semTests_1.0.0.zip
macOS binaries: r-release (arm64): semTests_1.0.0.tgz, r-oldrel (arm64): semTests_1.0.0.tgz, r-release (x86_64): semTests_1.0.0.tgz, r-oldrel (x86_64): semTests_1.0.0.tgz
Old sources: semTests archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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