MIIVefa

MIIVefa is data-driven algorithm 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.

Package and algorithm created by Ken Bollen, Katie Gates, & Lan Luo.

https://cran.r-project.org/web/packages/MIIVefa/vignettes/my-vignette.html

https://github.com/lluo0/MIIVefa