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-4.4-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'))

Peer review:

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

On CRAN:

3.70 score 1 stars 7 scripts 142 downloads 2 exports 65 dependencies

Last updated 9 months agofrom:776c51c9c9. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 12 2024
R-4.5-winOKNov 12 2024
R-4.5-linuxOKNov 12 2024
R-4.4-winOKNov 12 2024
R-4.4-macOKNov 12 2024
R-4.3-winOKNov 12 2024
R-4.3-macOKNov 12 2024

Exports:miivefaselect_scalingind

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2gluegtableisobandlabelinglatticelavaanlifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkMIIVsemminqamnormtmodelrmunsellnlmenloptrnnetnumDerivpbivnormpbkrtestpillarpkgconfigpurrrquadprogquantregR6RColorBrewerRcppRcppEigenrlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

MIIVefa and usage examples

Lan Luo

Rendered frommy-vignette.Rmdusingknitr::rmarkdownon Nov 12 2024.

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