Package: MIIVefa 0.1.2

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.

Authors:Lan Luo [aut, cre], Kathleen Gates [aut], Kenneth A. Bollen [aut]

MIIVefa_0.1.2.tar.gz
MIIVefa_0.1.2.zip(r-4.7)MIIVefa_0.1.2.zip(r-4.6)MIIVefa_0.1.2.zip(r-4.5)
MIIVefa_0.1.2.tgz(r-4.6-any)MIIVefa_0.1.2.tgz(r-4.5-any)
MIIVefa_0.1.2.tar.gz(r-4.7-any)MIIVefa_0.1.2.tar.gz(r-4.6-any)
MIIVefa_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
MIIVefa/json (API)
NEWS

# Install 'MIIVefa' in R:
install.packages('MIIVefa', repos = c('https://lluo0.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lluo0/miivefa/issues

On CRAN:

Conda:

3.70 score 1 stars 7 scripts 218 downloads 2 exports 74 dependencies

Last updated from:776c51c9c9. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK112
source / vignettesOK220
linux-release-x86_64OK144
macos-release-arm64OK169
macos-oldrel-arm64OK179
windows-develOK135
windows-releaseOK87
windows-oldrelOK74
wasm-releaseOK129

Exports:miivefaselect_scalingind

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegtableisobandlabelinglatticelavaanlifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkMIIVsemminqamnormtmodelrnlmenloptrnnetnumDerivpbivnormpbkrtestpillarpkgconfigpurrrquadprogquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

MIIVefa and usage examples

Lan Luo

Rendered frommy-vignette.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2023-09-16
Started: 2023-08-22