An alternative to Exploratory Factor Analysis (EFA) for metrical data in R. Drawing on characteristics of classical test theory, Exploratory Likert Scaling (ELiS) supports the user exploring multiple one-dimensional data structures. In common research practice, however, EFA remains the go-to method to uncover the (underlying) structure of a data set. Orthogonal dimensions and the potential of overextraction are often accepted as side effects. As described in Müller-Schneider (2001) <doi:10.1515/zfsoz-2001-0404>), ELiS confronts these problems. As a result, 'elisr' provides the platform to fully exploit the exploratory potential of the multiple scaling approach itself.
Version: 0.1.1 Depends: R (≥ 4.0.0) Imports: stats (≥ 4.0.0) Suggests: covr, devtools, knitr, pkgdown, psych, rmarkdown, testthat (≥ 3.0.0) Published: 2021-05-15 DOI: 10.32614/CRAN.package.elisr Author: Steven BiÃantz [aut, cre], Thomas Müller-Schneider [ctb] Maintainer: Steven BiÃantz <steven.bissantz at gmail.com> BugReports: https://github.com/sbissantz/elisr/issues License: GPL (≥ 3) URL: https://github.com/sbissantz/elisr NeedsCompilation: no Language: en, de Materials: README, NEWS CRAN checks: elisr results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=elisr to link to this page.
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