R: Information Plots for IRT Models

infoplot {psychotools}

R Documentation

Information Plots for IRT Models

Description

Base graphics plotting function for information plot visualization of IRT models.

Usage

  infoplot(object, what = c("categories", "items", "test"),
    ref = NULL, items = NULL, names = NULL, layout = NULL,
    xlim = NULL, ylim = NULL, col = NULL, lty = NULL, lwd = NULL,
    main = NULL, legend = TRUE, xlab = "Latent trait",
    ylab = "Information", add = FALSE, ...)

Arguments

`object`	a fitted model object of class `"raschmodel"`, `"rsmodel"` or `"pcmodel"`.
`what`	character, specifying the type of information to visualize.
`ref`	argument passed over to internal calls of `predict`.
`items`	character or numeric, specifying the items for which information curves should be visualized.
`names`	character, specifying labels for the items.
`layout`	matrix, specifying how the item or category information curves of different items should be arranged. If `null` and `what` is set to ``items'', the item information curves are overlayed within a single plot.
`xlim, ylim`	numeric, specifying the x and y axis limits.
`col`	character, specifying the colors of the test, item or category information curves.
`lty`	numeric, specifying the line type of the information curves.
`lwd`	numeric, specifying the line width of the information curves.
`main`	character, specifying the overall title of the plot.
`legend`	logical, specifying if a legend is drawn when multiple item information curves are overlayed. The labels in the legend correspond to the item names (which can be specified in the argument `names`).
`xlab, ylab`	character, specifying the x and y axis labels.
`add`	logical. If `TRUE`, new information curves are added to an existing plot. Only possible for a test or a single item information curve.
`...`	further arguments passed to internal calls of `matplot`

Details

The information plot visualization illustrates the test, item or category information as a function of the ability parameter θ under a certain IRT model. Further details on the computation of the displayed information can be found on the help page of the function predict.pcmodel.

Examples

## Load Verbal Aggression data
data("VerbalAggression", package = "psychotools")

## Fit Rasch and partial credit
## model to Verbal Aggression data
rmmod <- raschmodel(VerbalAggression$resp2)
pcmod <- pcmodel(VerbalAggression$resp)

## Category information plots for all items under
## the dichotomous Rasch model
plot(rmmod, type = "information", what = "categories")

## Category information plots for all items under
## the partial credit model
plot(pcmod, type = "information", what = "categories")

## Overlayed item information plots for the first six
## item of the Verbal Aggression data set under
## the partial credit model
plot(pcmod, type = "information", what = "items",
  items = 1:6)

## A comparison of the item information for the first six
## items under the dichotomous Rasch and the partial credit model
plot(pcmod, type = "information", what = "items",
  items = 1:6, xlim = c(-5, 5))
plot(rmmod, type = "information", what = "items",
  items = 1:6, lty = 2, add = TRUE)
legend(x = "topright", legend = c("PCM", "RM"), lty = 1:2, bty = "n")

## A comparison of the test information based on all items
## of the Verbal Aggression data set under the dichotomous Rasch
## and the partial credit model
plot(pcmod, type = "information", what = "test",
  items = 1:6, xlim = c(-5, 5))
plot(rmmod, type = "information", what = "test",
  items = 1:6, lty = 2, add = TRUE)
legend(x = "topright", legend = c("PCM", "RM"), lty = 1:2, bty = "n")