psych (version 1.0-97)

plot.psych: Plotting functions for the psych package of class ``psych"

Description

Combines several plotting functions into one for objects of class ``psych". This can be used to plot the results of fa, irt.fa, VSS, ICLUST, omega, factor.pa, or principal.

Usage

plot.psych(x,labels=NULL,...)
plot.irt(x,xlab,ylab,main,D,type=c("ICC","IIC","test"),cut=.3,labels,keys=NULL,...)
plot.poly(x,D,xlab,ylab,ylim,main,type=c("ICC","IIC","test"),cut=.3,labels,keys=NULL,...)

Arguments

x

The object to plot

labels

Variable labels

xlab

Label for the x axis -- defaults to Latent Trait

ylab

Label for the y axis

ylim

Specify the limits for the y axis

main

Main title for graph

type

ICC plots items, IIC plots item information, test plots test information, defaults to IIC for plot.irt, to ICC for plot.poly

D

The discrimination parameter

cut

Only plot item responses with discrimiantion greater than cut

keys

Used in plotting irt results from irt.fa.

...

other calls to plot

Value

• Graphic output for factor analysis, cluster analysis and item response analysis.

Details

Passes the appropriate values to plot. For plotting the results of irt.fa, there are three options: type = "ICC" (default) will plot the item characteristic respone function. type = "IIC" will plot the item information function, and type= "test" will plot the test information function.

These are calls to the generic plot function that are intercepted for objects of type "psych". More precise plotting control is available in the separate plot functions. plot may be used for psych objects returned from fa, irt.fa, ICLUST, omega, as well as principal

Objects from irt.fa are plotted according to "type" (Item informations, item characteristics, or test information). In addition, plots for selected items may be done if using the keys matrix. Plots of irt information return two invisible objects, the average area under the curve (the average information) for each item as well as where the item is most informative.

See Also

VSS.plot and factor.plot, cluster.plot, fa, irt.fa, VSS, ICLUST, omega, factor.pa, or principal

Examples

test.data <- Harman74.cor$cov
f4 <- fa(test.data,4)
plot(f4)

#not run
#data(bfi)
#e.irt <- irt.fa(bfi[11:15])  #just the extraversion items
#plot(e.irt)   #the information curves
#
#ic <- iclust(test.data,3)   #shows hierarchical structure 
#plot(ic)                    #plots loadings
#