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alphaci: Confidence Intervals for Coefficient Alpha and Standardized Alpha

Calculate confidence intervals for alpha and standardized alpha using asymptotic theory or the studentized bootstrap, with or without transformations. Supports the asymptotic distribution-free method of Maydeu-Olivares, et al. (2007) <doi:10.1037/1082-989X.12.2.157>, the pseudo-elliptical method of Yuan & Bentler (2002) <doi:10.1007/BF02294845>, and the normal method of van Zyl et al. (1999) <doi:10.1007/BF02296146>, for both coefficient alpha and standardized alpha.

Version: 1.0.1
Depends: R (≥ 3.5.0)
Imports: future.apply, matrixcalc
Suggests: covr, extraDistr, knitr, lavaan, psychTools, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-02-05
DOI: 10.32614/CRAN.package.alphaci
Author: Jonas Moss ORCID iD [aut, cre]
Maintainer: Jonas Moss <jonas.moss.statistics at gmail.com>
License: MIT + file LICENSE
URL: https://jonasmoss.github.io/alphaci/
NeedsCompilation: no
Materials: README
CRAN checks: alphaci results

Documentation:

Reference manual: alphaci.pdf
Vignettes: Simulation of confidence intervals.
Verifying the variances.

Downloads:

Package source: alphaci_1.0.1.tar.gz
Windows binaries: r-devel: alphaci_1.0.1.zip, r-release: alphaci_1.0.1.zip, r-oldrel: alphaci_1.0.1.zip
macOS binaries: r-release (arm64): alphaci_1.0.1.tgz, r-oldrel (arm64): alphaci_1.0.1.tgz, r-release (x86_64): alphaci_1.0.1.tgz, r-oldrel (x86_64): alphaci_1.0.1.tgz
Old sources: alphaci archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.