| plotnScree {nFactors} | R Documentation |
Plot a scree plot adding information about a non graphical nScree analysis.
plotnScree(nScree,
legend = TRUE,
ylab = "Eigenvalue",
xlab = "Component",
main = "Non Graphical Solutions to Scree Test"
)
nScree |
Results of a previous nScree analysis |
legend |
Logical indicator of the presence or not of a legend |
xlab |
Label of the x axis (default to "Component") |
ylab |
Label of the y axis (default to "Eigenvalue") |
main |
Main title (default to "Non Graphical Solutions to the Scree Test") |
Nothing returned.
Gilles Raiche, Universite du Quebec a Montreal raiche.gilles@uqam.ca, http://www.er.uqam.ca/nobel/r17165/
Raiche, G., Riopel, M. and Blais, J.-G. (2006). Non graphical solutions for the Cattell's scree test. Paper presented at the International Annual meeting of the Psychometric Society, Montreal. [http://www.er.uqam.ca/nobel/r17165/RECHERCHE/COMMUNICATIONS/]
plotuScree,
nScree,
plotParallel,
parallel
## 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)