Package: OptimalFactor Type: Package Title: Item Selection in Factor Analysis by Boosting and Specification Search Version: 1.5.0 Date: 2026-10-05 Authors@R: person("Jose", "Ventura-Leon", email = "jventuraleon@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-2996-4244")) Description: Provides an iterative optimization algorithm for exploratory and confirmatory factor analysis that follows a boosting approach inspired by machine learning. It uses a composite fit index whose weights adapt to the degrees of freedom and the sample size, following Kenny and McCoach (2003) and Shi, Lee and Maydeu-Olivares (2019) . It detects and removes problematic items (Heywood cases, cross-loadings, low loadings) with greedy or global search strategies, checks interfactor correlations, and supports ordinal data with WLSMV estimation and several rotation methods. A heuristic specification search for confirmatory models (MacCallum, 1986 ) explores move, drop and covariance operations across seed configurations. It also evaluates the resampling stability of the item selection, the recovery of a known or theoretical structure, and offers an optional conceptual analysis of removed items through a large language model service. License: GPL (>= 3) URL: https://github.com/jventural/OptimalFactor, https://jventural.github.io/OptimalFactor/ BugReports: https://github.com/jventural/OptimalFactor/issues Encoding: UTF-8 LazyData: true Depends: R (>= 4.0.0) Imports: lavaan, psych, dplyr, tidyr, ggplot2, stringr, parallel, stats, utils Suggests: testthat (>= 3.0.0), httr, jsonlite, R.utils, knitr, rmarkdown, semTools RoxygenNote: 7.3.2 VignetteBuilder: knitr Config/testthat/edition: 3 NeedsCompilation: no Packaged: 2026-10-24 21:06:42 UTC; root Author: Jose Ventura-Leon [aut, cre] (ORCID: ) Maintainer: Jose Ventura-Leon Repository: https://cran.r-universe.dev Date/Publication: 2026-10-24 16:30:08 UTC RemoteUrl: https://github.com/cran/OptimalFactor RemoteRef: HEAD RemoteSha: 8bfdcbfe058a911eb08f1824e9003822c6a46038