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 (source, R code)

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

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