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


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


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


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