plot.Itempool {irt} | R Documentation |
Plot Item Characteristic Curves or Test Characteristic Curve of an
Itempool
object
Description
plot.Itempool
plots the item characteristic curves (item response
curves) or test characteristic curve of an Itempool-class
object.
Usage
## S3 method for class 'Itempool'
plot(
x,
theta_range = c(-4, 4),
type = "icc",
tcc_prop_corr = FALSE,
focus_item = NULL,
title = "",
suppress_plot = FALSE,
legend_title = NULL,
base_r_graph = FALSE,
y_lim = NULL,
...
)
Arguments
x |
An |
theta_range |
Either a numeric vector of length two setting the
boundaries of x-axis, e.g. |
type |
The type of the graph. The default value is
|
tcc_prop_corr |
If |
focus_item |
A character string of the 'item_id' of the item to be
focused. If |
title |
Title of the plot. Set |
suppress_plot |
If |
legend_title |
The title of the plot's legend. |
base_r_graph |
If |
y_lim |
A numeric vector of length two representing the lower and upper bound of y-axis. |
... |
Additional arguments that will be passed to |
Value
Depending on the value of suppress_plot
function either prints
the item characteristic curve or returns the plot object.
Author(s)
Emre Gonulates
Examples
ip <- generate_ip(n = sample(10:15,1))
plot(ip)
# Additional arguments will passed to geom_line
plot(ip, size = .25, alpha = 0.3)
# Set the boundaries of the graph
plot(ip, theta_range = c(-2, 2))
# alternatively provide theta values
plot(ip, theta_range = seq(-6, 6, by = 0.25))
# Test Characteristic Curve
plot(ip, type = "tcc")
# Proportion correct for test characteristic curve
plot(ip, type = "tcc", tcc_prop_corr = TRUE)
# Plot histogram of item parameters
plot(ip, type = "hist")
## Not run:
# Item parameter summary
ip <- generate_ip(n = 200)
plot(ip, type = "pars")
plot(ip, type = "pars", dotsize = .75)
plot(ip, type = "pars", focus_item = "Item_22")
# Use base R graphics
plot(ip, type = "pars", base_r_graph = TRUE)
# # Remove the legend altogether
# plot(ip, suppress_plot = TRUE) + ggplot2::theme(legend.position="none")
# # Change the labels:
# plot(ip, suppress_plot = TRUE) +
# ylab("Probability") + xlab("Ability Score")
## End(Not run)