plotICC {eRm}R Documentation

ICC and Goodness-of-Fit Plots

Description

Various plot functions for visualizing the item characteristic curves

Usage

## S3 method for class 'Rm':
plotICC(object, item.subset = "all", empirical = FALSE, xlim = c(-4, 4), ylim = c(0, 1), xlab = "Latent Dimension", ylab = "Probability to Solve", ...)
## S3 method for class 'dRm':
plotjointICC(object, item.subset = "all", legend = TRUE, xlim = c(-4, 4), ylim = c(0, 1), xlab = "Latent Dimension", ylab = "Probability to Solve", lty = 1, ...)

Arguments

object object of class Rm or dRm
item.subset Subset of items to be plotted. Either a numeric vector indicating the column in X or a character vector indiciating the column name. If "all", all items are plotted.
empirical Option for plotting the empirical ICCs for objects of class dRm
legend If TRUE, legend is provided, otherwise the ICCs are labeled.
xlab Label of the x-axis.
ylab Label of the y-axis.
xlim Range of person parameters.
ylim Range for probability to solve.
lty Line type.
... Additional plot parameters.

Details

Value

Note

Author(s)

Patrick Mair, Reinhold Hatzinger

References

See Also

plotGOF

Examples


# Rating scale model, ICC plot for all items
data(rsmdat)
res <- RSM(rsmdat)
plotICC(res)

# Rasch model with empirical ICCs
newdata <- matrix(sample(0:1, 1000, replace = TRUE), ncol = 5)
res <- RM(newdata)
plotICC(res, empirical = TRUE)

# Joint ICC plot for items 2, 6, 8, and 15 for a Rasch model
data(raschdat1)
res <- RM(raschdat1)
plotjointICC(res, item.subset = c(2,6,8,15))


[Package eRm version 0.9.1.1 Index]