mirt (version 1.1)

plot-method: Plot various test implied functions from models

Description

plot(x, y, type = 'info', npts = 50, theta_angle = 45, which.items = 1:ncol(x@data), rot = list(xaxis = -70, yaxis = 30, zaxis = 10), facet_items = FALSE, auto.key = TRUE, ...)

Arguments

x

an object of class ExploratoryClass, ConfirmatoryClass or MultipleGroupClass

type

type of plot to view; can be 'info' to show the test information function, 'infocontour' for the test information contours, 'SE' for the test standard error function, 'trace' and 'infotrace

theta_angle

numeric values ranging from 0 to 90 used in plot. If a vector is used then a bubble plot is created with the summed information across the angles specified (e.g., theta_angle = seq(0, 90, by=10))

npts

number of quadrature points to be used for plotting features. Larger values make plots look smoother

rot

allows rotation of the 3D graphics

which.items

numeric vector indicating which items to be used when plotting. Default is to use all available items

facet_items

logical; apply grid of plots accross items? If FALSE, items will be placed in one plot for each group

auto.key

logical parameter passed to the lattice package

...

additional arguments to be passed

Examples

x <- mirt(Science, 1)
plot(x)
plot(x, type = 'trace')
plot(x, type = 'infotrace')
plot(x, type = 'infotrace', facet_items = TRUE)
plot(x, type = 'infoSE')

set.seed(1234)
group <- sample(c('g1','g2'), nrow(Science), TRUE)
x2 <- multipleGroup(Science, 1, group)
plot(x2)
plot(x2, type = 'trace')
plot(x2, type = 'trace', which.items = 1:2)
plot(x2, type = 'score')

x3 <- mirt(Science, 2)
plot(x3)
plot(x3, type = 'SE')