eRm (version 0.9.0)

plotICC: 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.

Value

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, 6000, replace = TRUE), ncol = 6)
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))