semanticfa: Semantic Factor Analysis of Language Model Embeddings
Performs exploratory factor analysis on language model embeddings
of psychological scale items. Embeds item text with sentence transformers
or other language models, transforms the embeddings into item-by-item
similarity matrices, and extracts latent factor structure via standard
exploratory factor analysis. Supports embedding-adapted parallel analysis,
several similarity transforms (atomic reversed, SQuID centering,
mean-centered Pearson), and fit diagnostics tailored to embedding matrices
(TEFI, RMSR, CAF, McDonald's omega). The underlying methods are documented
with full citations in the corresponding function help pages. Returns
objects compatible with 'psych' and 'EFAtools' workflows.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
GPArotation, grDevices, graphics, psych, reticulate (≥
1.41.0), Rtsne, stats, utils, uwot, withr |
| Suggests: |
digest, EFAtools, EGAnet, httr2, knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2026-06-15 |
| DOI: |
10.32614/CRAN.package.semanticfa |
| Author: |
Devon Yanitski 
[aut, cre],
Chris Westbury [aut] |
| Maintainer: |
Devon Yanitski <dyanitsk at ualberta.ca> |
| BugReports: |
https://github.com/devon7y/semanticfa/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/devon7y/semanticfa |
| NeedsCompilation: |
no |
| Citation: |
semanticfa citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
semanticfa results |
Documentation:
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