Last data update: 2014.03.03

R: Scree Plot According to a nScree Object Class
plotnScreeR Documentation

Scree Plot According to a nScree Object Class

Description

Plot a scree plot adding information about a non graphical nScree analysis.

Usage

 plotnScree(nScree, 
            legend = TRUE,
            ylab   = "Eigenvalues",
            xlab   = "Components",
            main   = "Non Graphical Solutions to Scree Test"
            )                    
 

Arguments

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")

Value

Nothing returned.

Author(s)

Gilles Raiche
Centre sur les Applications des Modeles de Reponses aux Items (CAMRI)
Universite du Quebec a Montreal
raiche.gilles@uqam.ca, http://www.er.uqam.ca/nobel/r17165/

References

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/]

See Also

plotuScree, nScree, plotParallel, parallel

Examples

## 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)
 

Results