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FactorAssumptions  

Set of Assumptions for Factor and Principal Component Analysis
View on CRAN: Click here


Download and install FactorAssumptions package within the R console
Install from CRAN:
install.packages("FactorAssumptions")

Install from Github:
library("remotes")
install_github("cran/FactorAssumptions")

Install by package version:
library("remotes")
install_version("FactorAssumptions", "2.0.1")



Attach the package and use:
library("FactorAssumptions")
Maintained by
Jose Storopoli
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-06
Latest Update: 2022-03-08
Description:
Tests for Kaiser-Meyer-Olkin (KMO) and communalities in a dataset. It provides a final sample by removing variables in a iterable manner while keeping account of the variables that were removed in each step. It follows the best practices and assumptions according to Hair, Black, Babin & Anderson (2018, ISBN:9781473756540).
How to cite:
Jose Storopoli (2020). FactorAssumptions: Set of Assumptions for Factor and Principal Component Analysis. R package version 2.0.1, https://cran.r-project.org/web/packages/FactorAssumptions. Accessed 03 Feb. 2025.
Previous versions and publish date:
1.1.2 (2020-03-06 18:10)
Other packages that cited FactorAssumptions R package
View FactorAssumptions citation profile
Other R packages that FactorAssumptions depends, imports, suggests or enhances
Complete documentation for FactorAssumptions
Functions, R codes and Examples using the FactorAssumptions R package
Some associated functions: communalities_optimal_solution . kmo . kmo_optimal_solution . 
Some associated R codes: communalities_optimal_solution.R . kmo.R . kmo_optimal_solution.R .  Full FactorAssumptions package functions and examples
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