FactorAssumptions | What is KMO and Communalities? | Loading an example dataset | Performing the KMO Assumptions | Performing the Communalities Assumptions | References
Package: FactorAssumptions 2.0.1
FactorAssumptions: Set of Assumptions for Factor and Principal Component Analysis
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).
Authors:
FactorAssumptions_2.0.1.tar.gz
FactorAssumptions_2.0.1.zip(r-4.7-any)FactorAssumptions_2.0.1.zip(r-4.6-any)FactorAssumptions_2.0.1.zip(r-4.5-any)
FactorAssumptions_2.0.1.tgz(r-4.6-any)FactorAssumptions_2.0.1.tgz(r-4.5-any)
FactorAssumptions_2.0.1.tar.gz(r-4.7-any)FactorAssumptions_2.0.1.tar.gz(r-4.6-any)
FactorAssumptions_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
FactorAssumptions/json (API)
| # Install 'FactorAssumptions' in R: |
| install.packages('FactorAssumptions', repos = c('https://storopoli.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/storopoli/factorassumptions/issues
Last updated from:18115c73a4. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 105 | ||
| source / vignettes | OK | 145 | ||
| linux-release | OK | 104 | ||
| macos-release | OK | 133 | ||
| macos-oldrel | OK | 189 | ||
| windows-devel | OK | 62 | ||
| windows-release | OK | 67 | ||
| windows-oldrel | OK | 59 | ||
| wasm-release | OK | 80 |
Exports:communalities_optimal_solutionkmokmo_optimal_solution
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calculates the Optimal Solution for Communalities in a Dataframe | communalities_optimal_solution |
| Calculates the Kayser-Meyer-Olkin (KMO) | kmo |
| Calculates the Optimal Solution for Kayser-Meyer-Olkin (KMO) in a Dataframe | kmo_optimal_solution |