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psychotools (version 0.4-0)

piplot: Person-Item Plots for IRT Models

Description

Base graphics plotting function for person-item plot visualization of IRT models.

Usage

piplot(object, ref = NULL, items = NULL, xlim = NULL, names = NULL, labels = TRUE, main = "Person-Item Plot", xlab = "Latent trait", abbreviate = FALSE, cex.axis = 0.8, cex.text = 0.5, cex.points = 1.5, ...)

Arguments

object
a fitted model object of class "raschmodel", "rsmodel" or "pcmodel".
ref
argument passed over to internal calls of threshpar and itempar.
items
character or numeric, specifying the items which should be visualized in the person-item plot.
xlim
numeric, specifying the x axis limits.
names
character, specifying labels for the items.
labels
logical, whether to draw the number of the threshold as text below the threshold.
main
character, specifying the overall title of the plot.
xlab
character, specifying the x axis labels.
abbreviate
logical or numeric, specifying whether object names are to be abbreviated. If numeric this controls the length of the abbreviation.
cex.axis
numeric, the magnification to be used for the axis notation relative to the current setting of cex.
cex.text
numeric, the magnification to be used for the symbols relative to the current setting of cex.
cex.points
numeric, the magnification to be used for the points relative to the current setting of cex.
...
further arguments passed to internal calls of lines, points and text

Details

The person-item plot visualization illustrates the distribution of the person parameters against the absolute item threshold parameters under a certain data set and IRT model.

See Also

curveplot, regionplot, profileplot, infoplot

Examples

Run this code
## Verbal aggression data
data("VerbalAggression", package = "psychotools")

## Fit a partial credit model to VerbalAggression data
pcmod <- pcmodel(VerbalAggression$resp)

## Create a person-item plot visualization of the fitted PCM
plot(pcmod, type = "piplot")

## Just visualize the first six items
plot(pcmod, type = "piplot", ref = 1:6)

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