elisr: Exploratory Likert Scaling

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
Author: Steven Bißantz [aut, cre], Thomas Müller-Schneider [ctb]
Maintainer: Steven Bißantz <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

Downloads:

Reference manual: elisr.pdf
Vignettes: elisr companion
Package source: elisr_0.1.1.tar.gz
Windows binaries: r-devel: elisr_0.1.1.zip, r-release: elisr_0.1.1.zip, r-oldrel: elisr_0.1.1.zip
macOS binaries: r-release (arm64): elisr_0.1.1.tgz, r-release (x86_64): elisr_0.1.1.tgz, r-oldrel: elisr_0.1.1.tgz
Old sources: elisr archive

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