Package: semTests 2.0.0

Jonas Moss

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. Score and criterion-difference tests of parameter restrictions are also available, including restrictions in misspecified models.

Authors:Jonas Moss [aut, cre], Njål Foldnes [ctb], Steffen Grønneberg [ctb]

semTests_2.0.0.tar.gz
semTests_2.0.0.zip(r-4.7-any)semTests_2.0.0.zip(r-4.6-any)
semTests_2.0.0.tar.gz(r-4.7-any)semTests_2.0.0.tar.gz(r-4.6-any)
semTests_2.0.0.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://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jonasmoss/semtests/issues

On CRAN:

Conda:

4.41 score 43 scripts 202 downloads 4 exports 6 dependencies

Last updated from:d777c2b55e. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develOK199
source / vignettesOK197
linux-releaseOK163
windows-develOK164
windows-releaseOK154
wasm-releaseOK94

Exports:inference_controlpvaluespvalues_nestedsemtest

Dependencies:lavaanMASSmnormtnumDerivpbivnormquadprog

Getting started with semTests
What semTests does | Overall fit | Choosing a test | Nested models | Other estimators | References
Rendered fromsemTests.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-06-09

Missing data with FIML
Scope | A model with missing values | Observed information | Observed predictors | Nested models: is growth linear? | Several groups | References
Rendered fromfiml-missing-data.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-07-19

Ordinal indicators and measurement invariance
Scope | Data | Overall fit | Mixed indicators | Pairwise deletion | Measurement invariance | References
Rendered fromcategorical-data.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-07-19

Score and criterion tests
What do you want to test? | One restriction, two tests | Score: evaluate the restricted fit | Criterion difference: compare both fits | What if the factor model is misspecified? | How the statistic and its reference are formed | Conventions: inference_control() | Choosing a p-value calibration | Global exact fit | Missing data and estimated fitting weights | Inspecting a result | References
Rendered fromscore-criterion.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-10-29