pre_factor: Evaluate if data are appropriate for PCA / Factor analysis

In radiant-rstats/radiant.multivariate: Multivariate Menu for Radiant: Business Analytics using R and Shiny

Evaluate if data are appropriate for PCA / Factor analysis

Description

Evaluate if data are appropriate for PCA / Factor analysis

Usage

pre_factor(
  dataset,
  vars,
  hcor = FALSE,
  data_filter = "",
  envir = parent.frame()
)

Arguments

dataset	Dataset
vars	Variables to include in the analysis
hcor	Use polycor::hetcor to calculate the correlation matrix
data_filter	Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")
envir	Environment to extract data from

Details

See https://radiant-rstats.github.io/docs/multivariate/pre_factor.html for an example in Radiant

Value

A list with all variables defined in the function as an object of class pre_factor

See Also

summary.pre_factor to summarize results

plot.pre_factor to plot results

Examples

pre_factor(shopping, "v1:v6") %>% str()

radiant-rstats/radiant.multivariate documentation built on Nov. 29, 2023, 9:52 p.m.