semTests: Robust Test Statistics for Structural Equation Models
Supports penalized eigenvalue block-averaging and penalized
regression p-values (Foldnes, Moss, Grønneberg, 2024)
<doi:10.1080/10705511.2024.2372028>, including their extension to nested
model comparison (Foldnes, Grønneberg, Moss, 2026)
<doi:10.3758/s13428-026-02968-4>, as well as traditional p-values such as
Satorra-Bentler. All p-values can be calculated using unbiased or biased
gamma estimates (Du, Bentler, 2022) <doi:10.1080/10705511.2022.2063870> and
two choices of chi square statistics. The tests apply to any
minimum-discrepancy estimator – ML, GLS, ULS, and categorical WLSMV/DWLS –
with experimental support for full-information maximum-likelihood (FIML) fits
under missing data.
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