Plot Hull Plot for Factor Analysis

This function creates a Hull plot to visualize the relationship between the Comparative Fit Index (CFI) and the degrees of freedom (df) for a range of models with different numbers of factors. The Hull plot helps in assessing model fit and identifying optimal models.

# S3 method for class 'Hull'
plot(x, ...)

Arguments

x

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

...

Additional arguments to be passed to the plotting function.

Value

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

See also

Hull

Examples

library(EFAfactors)
set.seed(123)

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

response <- as.matrix(data.bfi[, 1:25]) ## loading 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{
 Hull.obj <- CD(response)
#> 
CD is simulating data: nfact= 1/10
CD is simulating data: nfact= 2/10
CD is simulating data: nfact= 3/10
CD is simulating data: nfact= 4/10
CD is simulating data: nfact= 5/10
CD is simulating data: nfact= 6/10
CD is simulating data: nfact= 7/10
CD is simulating data: nfact= 8/10
CD is simulating data: nfact= 9/10
CD is simulating data: nfact=10/10
#> The number of factors suggested by CD is 9 .

 ## Hull plot
 plot(Hull.obj)


# }