psych (version 2.6.1)

iclust.diagram: Draw an ICLUST hierarchical cluster structure diagram

Description

Given a cluster structure determined by ICLUST, create a graphic structural diagram using graphic functions in the psych package To create dot code to describe the ICLUST output with more precision, use ICLUST.graph. If Rgraphviz has been successfully installed, the alternative is to use ICLUST.rgraph.

Usage

iclust.diagram(ic, labels = NULL, short = FALSE, digits = 2, cex = NULL, 
    min.size = NULL,
     e.size =1,
     colors=c("black","blue"), 
     main = "ICLUST diagram",
     cluster.names=NULL,marg=c(.5,.5,1.5,.5),plot=TRUE, bottomup=TRUE,
                both=TRUE,pos=NULL,...)

Value

Graphical output summarizing the hierarchical cluster structure. The graph is drawn using the diagram functions (e.g., dia.curve, dia.arrow, dia.rect, dia.ellipse ) created as a work around to Rgraphviz.

Also returned (invisibly) is a vector of variable names ordered by their location in the tree diagram. The plot option suppresses the plot for speed.

Details

iclust.diagram provides most of the power of ICLUST.rgraph without the difficulties involved in installing Rgraphviz. It is called automatically from ICLUST.

Following a request by Michael Kubovy, cluster.names may be specified to replace the normal C1 ... Cn names.

If access to a dot language graphics program is available, it is probably better to use the iclust.graph function to get dot output for offline editing.

Until 3/11/23 arrows went from clusters to items. The default value for bottomup has been changed to draw from items to clusters. To draw the old way, set bottomup=TRUE.

References

Revelle, W. Hierarchical Cluster Analysis and the Internal Structure of Tests. Multivariate Behavioral Research, 1979, 14, 57-74.

See Also

ICLUST

Examples

v9 <- sim.hierarchical()
v9c <- ICLUST(v9)
test.data <- Harman74.cor$cov
ic.out <- ICLUST(test.data)
#now show how to relabel clusters
ic.bfi <- iclust(bfi[1:25],beta=3) #find the clusters
cluster.names <- rownames(ic.bfi$results) #get the old names
#change the names to the desired ones
cluster.names[c(16,19,18,15,20)] <- c("Neuroticism","Extra-Open","Agreeableness",
      "Conscientiousness","Open")
#now show the new names
iclust.diagram(ic.bfi,cluster.names=cluster.names,min.size=4,e.size=1.75)
#just use the diagram function (which calls iclust.diagram).
#Add item content using the labels parameter
diagram(ic.bfi,labels=bfi.dictionary[,2],cluster.names=cluster.names, 
       min.size=4,e.size=1.5, main="ICLUST of the BFI")