This package is considered a duplicate. The official version of this package is found at:https://devon7y.r-universe.dev/semanticfa

Package: semanticfa 0.1.1

Devon Yanitski

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.

Authors:Devon Yanitski [aut, cre], Chris Westbury [aut]

semanticfa_0.1.1.tar.gz
semanticfa_0.1.1.tar.gz(r-4.7-any)semanticfa_0.1.1.tar.gz(r-4.6-any)
semanticfa_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
semanticfa/json (API)

# Install 'semanticfa' in R:

install.packages('semanticfa', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/devon7y/semanticfa/issues

Datasets:

big5 - IPIP Big Five 50-Item Inventory with Qwen3 Embeddings

On CRAN:

3.00 score 5 scripts 218 downloads 21 exports 28 dependencies

Last updated from:3548f314dd. Checks:4 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	OK	224
source / vignettes	OK	276
linux-release-x86_64	OK	218
wasm-release	OK	209

Exports:as_psych sfa sfa_anchor sfa_clear_cache sfa_congruence sfa_corplot sfa_dimselect sfa_embed sfa_install_python sfa_item_fit sfa_itemplot sfa_jinglejangle sfa_load_npz sfa_nfactors sfa_nli_matrix sfa_parallel sfa_project sfa_redundancy sfa_similarity sfa_simplify sfa_tsneplot

Dependencies:BH digest dqrng FNN GPArotation here irlba jsonlite lattice Matrix mnormt nlme png psych rappdirs Rcpp RcppAnnoy RcppEigen RcppProgress RcppTOML reticulate rlang rprojroot RSpectra Rtsne sitmo uwot withr

Getting Started with semanticfa

Rendered fromintroduction.Rmdusingknitr::rmarkdown

Last update: 2026-07-03
Started: 2026-06-15

Help page	Topics
semanticfa: Semantic Factor Analysis of Language Model Embeddings	semanticfa-package semanticfa
Coerce to psych fa Object	as_psych as_psych.sfa
IPIP Big Five 50-Item Inventory with Qwen3 Embeddings	big5
Semantic Factor Analysis	sfa
Construct-Label and Centroid Anchoring	sfa_anchor
Clear Embedding Cache	sfa_clear_cache
Compare Semantic and Empirical Factor Structures	sfa_congruence
Heatmap of an Item-by-Item Similarity Matrix	sfa_corplot
Embedding-Dimension Selection by EGA Depth Optimization	sfa_dimselect
Embed Item Text with a Language Model	sfa_embed
Provision the Python Environment for Embedding	sfa_install_python
Vet a Candidate Scale Item Before Data Collection	sfa_item_fit
2-D Item Map (t-SNE, UMAP, PCA, or MDS)	sfa_itemplot sfa_tsneplot
Detect Jingle and Jangle Fallacies Across Scales	sfa_jinglejangle
Load Pre-generated Embeddings from a NumPy .npz File	sfa_load_npz
Unified Factor Retention Diagnostics	sfa_nfactors
Signed Item Similarity from Natural Language Inference	sfa_nli_matrix
Embedding-Adapted Parallel Analysis	sfa_parallel
Semantic Projection onto Bipolar Axes	sfa_project
Detect Redundant (Near-Duplicate) Items	sfa_redundancy
Compute Embedding Similarity Matrix	sfa_similarity
Response-Free Scale Simplification	sfa_simplify

Package: semanticfa 0.1.1

semanticfa: Semantic Factor Analysis of Language Model Embeddings

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)