EFAfactors (version 1.2.3)

plot.KGC: Plot Kaiser-Guttman Criterion (KGC) Plot

Description

This function generates a Kaiser-Guttman Criterion (KGC) plot to visualize the eigenvalues of the actual data. The Kaiser-Guttman Criterion, also known as the Kaiser criterion, suggests retaining factors with eigenvalues greater than 1. The plot shows the eigenvalues and includes a reference line at 1 to indicate the threshold for factor retention.

Usage

# S3 method for KGC
plot(x, ...)

Value

None. This function is used for side effects (plotting).

Arguments

x

An object of class KGC, representing the results to be plotted.

...

Additional arguments to be passed to the plotting function.

See Also

KGC

Examples

library(EFAfactors)
set.seed(123)

## Take the data.bfi dataset as an example.
data(data.bfi)

response <- as.matrix(data.bfi[, 1:25]) ## Load data
response <- na.omit(response) ## Remove samples with NA/missing values

## Transform the scores of reverse-scored items to normal scoring
response[, c(1, 9, 10, 11, 12, 22, 25)] <- 6 - response[, c(1, 9, 10, 11, 12, 22, 25)] + 1

# \donttest{
  KGC.obj <- KGC(response)

  ## Plot the Kaiser-Guttman Criterion
  plot(KGC.obj)
# }