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-4.5)MIIVefa_0.1.2.zip(r-4.4)MIIVefa_0.1.2.zip(r-4.3)
MIIVefa_0.1.2.tgz(r-4.5-any)MIIVefa_0.1.2.tgz(r-4.4-any)MIIVefa_0.1.2.tgz(r-4.3-any)
MIIVefa_0.1.2.tar.gz(r-4.5-noble)MIIVefa_0.1.2.tar.gz(r-4.4-noble)
MIIVefa_0.1.2.tgz(r-4.4-emscripten)MIIVefa_0.1.2.tgz(r-4.3-emscripten)
MIIVefa.pdf |MIIVefa.html
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:

3.70 score 1 stars 7 scripts 186 downloads 2 exports 68 dependencies

Last updated 1 years agofrom:776c51c9c9. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 10 2025
R-4.5-winOKFeb 10 2025
R-4.5-macOKFeb 10 2025
R-4.5-linuxOKFeb 10 2025
R-4.4-winOKFeb 10 2025
R-4.4-macOKFeb 10 2025
R-4.3-winOKFeb 10 2025
R-4.3-macOKFeb 10 2025

Exports:miivefaselect_scalingind

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2gluegtableisobandlabelinglatticelavaanlifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkMIIVsemminqamnormtmodelrmunsellnlmenloptrnnetnumDerivpbivnormpbkrtestpillarpkgconfigpurrrquadprogquantregR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

MIIVefa and usage examples

Rendered frommy-vignette.Rmdusingknitr::rmarkdownon Feb 10 2025.

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