Introduction | Basic usage: goodness of fit | The test-name grammar | Nested model comparison | Other estimators and missing data (experimental) | References
Package: semTests 0.9.0
Jonas Moss
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.
Authors:
semTests_0.9.0.tar.gz
semTests_0.9.0.zip(r-4.7)semTests_0.9.0.zip(r-4.6)semTests_0.9.0.zip(r-4.5)
semTests_0.9.0.tgz(r-4.6-any)semTests_0.9.0.tgz(r-4.5-any)
semTests_0.9.0.tar.gz(r-4.7-any)semTests_0.9.0.tar.gz(r-4.6-any)
semTests_0.9.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
semTests/json (API)
| # Install 'semTests' in R: |
| install.packages('semTests', repos = c('https://jonasmoss.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jonasmoss/semtests/issues
Last updated from:9456a72af1. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 210 | ||
| source / vignettes | OK | 164 | ||
| linux-release-x86_64 | OK | 204 | ||
| macos-release-arm64 | OK | 185 | ||
| macos-oldrel-arm64 | OK | 192 | ||
| windows-devel | OK | 189 | ||
| windows-release | OK | 212 | ||
| windows-oldrel | OK | 235 | ||
| wasm-release | OK | 104 |
Exports:pvaluespvalues_nested
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Print method for p-values from 'pvalues()' / 'pvalues_nested()'. | print.semTests_pvalues |
| Calculate _p_-values for one or two 'lavaan' objects. | pvalues pvalues_nested |