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MIIVefa: Exploratory Factor Analysis Using Model Implied Instrumental Variables

Data-driven approach for Exploratory Factor Analysis (EFA) that uses Model Implied Instrumental Variables (MIIVs). The method starts with a one factor model and arrives at a suggested model with enhanced interpretability that allows cross-loadings and correlated errors.

Version: 0.1.2
Depends: R (≥ 4.2.0)
Imports: MIIVsem
Suggests: knitr, rmarkdown, spelling, testthat (≥ 3.0.0), mnormt, lavaan, MPsychoR
Published: 2024-02-17
DOI: 10.32614/CRAN.package.MIIVefa
Author: Lan Luo [aut, cre], Kathleen Gates [aut], Kenneth A. Bollen [aut]
Maintainer: Lan Luo <lanl27 at live.unc.edu>
BugReports: https://github.com/lluo0/MIIVefa/issues
License: MIT + file LICENSE
URL: https://github.com/lluo0/MIIVefa/
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: MIIVefa results

Documentation:

Reference manual: MIIVefa.pdf
Vignettes: MIIVefa and usage examples

Downloads:

Package source: MIIVefa_0.1.2.tar.gz
Windows binaries: r-devel: MIIVefa_0.1.2.zip, r-release: MIIVefa_0.1.2.zip, r-oldrel: MIIVefa_0.1.2.zip
macOS binaries: r-release (arm64): MIIVefa_0.1.2.tgz, r-oldrel (arm64): MIIVefa_0.1.2.tgz, r-release (x86_64): MIIVefa_0.1.2.tgz, r-oldrel (x86_64): MIIVefa_0.1.2.tgz
Old sources: MIIVefa archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=MIIVefa to link to this page.

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.
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