Complete skill family for confirmatory factor analysis (CFA) and measurement model evaluation. Use when the user asks for CFA, latent factor validation, measurement models, factor loadings, convergent/discriminant validity, or measurement invariance. Uses a two-step structure: testing for initial diagnostics, analyzing for full pipeline.
VeraSuperHub npx skillmds@latest add verasuperhub/vera-data-cfa-pipelining Open-source skill.
This domain contains:
vera-data-cfa-reviewing for identification checks, estimator selection, and an
initial CFA fit with interpreted fit indices and standardized loadingsvera-data-cfa-generating for reliability/validity, invariance, model
comparison, and manuscript-ready methods/resultsPrimary engine: lavaan in R. Secondary Python support may use semopy, but
R is the default path whenever full SEM features are needed.
VeraSuperHub/stat-research-pipeline/tree/main/vera-stat-research-skillset/vera-data-cfa-pipelining commit 98fb0af0c3