## INITIALISATION
data(dFactors) # Load the nFactors dataset
attach(dFactors)
vect <- Raiche # Use the second example from Buja and Eyuboglu
# (1992, p. 519, nsubjects not specified by them)
eigenvalues <- vect$eigenvalues # Extract the observed eigenvalues
nsubjects <- vect$nsubjects # Extract the number of subjects
variables <- length(eigenvalues) # Compute the number of variables
rep <- 100 # Number of replications for the parallel analysis
cent <- 0.95 # Centile value of the parallel analysis
## PARALLEL ANALYSIS (qevpea for the centile criterion, mevpea for the mean criterion)
aparallel <- parallel(var = variables,
subject = nsubjects,
rep = rep,
cent = cent)$eigen$qevpea # The 95 centile
## NOMBER OF FACTORS RETAINED ACCORDING TO DIFFERENT RULES
results <- nScree(eig = eigenvalues,
aparallel = aparallel
)
results
## PLOT ACCORDING TO THE nScree CLASS
plotnScree(results)
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