plot_emprical_icc
plots empirical item or test characteristic curve.
plot_empirical_icc(
resp,
item,
type = "eicc",
bins = 10,
ip = NULL,
theta = NULL,
title = "",
suppress_plot = FALSE,
x_axis_scale = NULL,
n_dodge = 1,
...
)
Response matrix.
The column number, column name or the 'id' of the the item that should be plotted.
The type of the graph that will be plotted.
"eicc"
Plot empirical item characteristic curve. Examinees will be put into bins based on their total raw scores and the proportion of examinees who correctly answered an item for each bin will be plotted.
Plot Observed p-values vs. expected p-values
grouped into bins based on total raw scores or theta scores.
This plot requires an Itempool-class
object.
Optionally, provide theta
vector, otherwise examinee abilities
will be estimated by est_ability(..., type = "eap")
. This will
slow down the plotting function.
An integer larger than 2 representing of ability groups examinees
should be grouped into. The default is 10
. The maximum value of
bins + 1
is the number of possible total scores.
An Itempool-class
object that is needed for some
plots.
A vector of examinee abilities.
Title of the plot
If FALSE
the function will print the plot. If
TRUE
, function will return the plot object. Default value is
FALSE
.
Set the scale of the x-axis. The default value is
NULL
. For total score it will be defaulted to "percent"
.
"percent"
Percent interval.
"number"
Numbers between 1 and bins
"theta"
Theta values equally divided into bins.
the middle value of the bin is shown in the x-axis. For example, if
bins = 10
, the first tick of the x-axis will be the mean of
minimum theta value and 10th percentile theta value.
This is the only option for type = "oep"
.
The number of lines the x-axis tick labels should be written
to. This is especially useful if the x-axis tick labels overlap with each
other. The default value is 1
, which means all of the labels are
written on the same line.
Extra parameters that will pass to geom_line
.
Depending on the value of suppress_plot
function either prints
the empirical item or test characteristic curve or returns the plot object.
# NOT RUN {
# Plot the information function of an item
resp <- sim_resp(ip = generate_ip(model = "3PL", n = 20),
theta = rnorm(10000))
plot_empirical_icc(resp, 3)
# Change the number of bins
plot_empirical_icc(resp, 4, bins = 15)
# }
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