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

On CRAN:

2 exports 1 stars 1.10 score 64 dependencies 7 scripts 180 downloads

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

Exports:miivefaselect_scalingind

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelavaanlifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkMIIVsemminqamnormtmodelrmunsellnlmenloptrnnetnumDerivpbivnormpbkrtestpillarpkgconfigpurrrquadprogquantregR6RColorBrewerRcppRcppEigenrlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr