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Plot All Item Information Curves Overlaid from exametrika

Source: R/ICCtoTIC.R
plotIIC_overlay_gg.Rd

This function takes exametrika IRT or GRM output as input and generates an overlay plot of all Item Information Curves (IIC) using ggplot2. All item curves are displayed on a single graph for easy comparison.

Usage

plotIIC_overlay_gg(
  data,
  items = NULL,
  xvariable = c(-4, 4),
  title = TRUE,
  colors = NULL,
  linetype = "solid",
  show_legend = TRUE,
  legend_position = "right"
)

Arguments

data

An object of class c("exametrika", "IRT") from exametrika::IRT() or c("exametrika", "GRM") from exametrika::GRM().

items

Numeric vector specifying which items to plot. If NULL (default), all items are plotted.

xvariable

A numeric vector of length 2 specifying the range of the x-axis (ability). Default is c(-4, 4).

title

Logical or character. If TRUE (default), display an auto-generated title. If FALSE, no title. If a character string, use it as a custom title.

colors

Character vector of colors for each item. If NULL (default), a colorblind-friendly palette is used.

linetype

Character or numeric specifying the line type. Can be a single value for all items or a vector for each item. Default is "solid".

show_legend

Logical. If TRUE (default), display the legend.

legend_position

Character. Position of the legend. One of "right" (default), "top", "bottom", "left", "none".

Value

A single ggplot object showing all Item Information Curves overlaid on one graph.

Details

This function is similar to calling plot(IRT_result, type = "IIF", overlay = TRUE) or plot(GRM_result, type = "IIF", overlay = TRUE) in the exametrika package, but returns a ggplot2 object that can be further customized.

The Item Information Function indicates how precisely an item measures ability at each point on the theta scale. Items with higher discrimination parameters provide more information. The peak of the information curve occurs near the item's difficulty parameter.

See also

plotIIC_gg, plotICC_gg

Examples

library(exametrika)
# \donttest{
# IRT example
result_irt <- IRT(J15S500, model = 3)
#> No ID column detected. All columns treated as response data. Sequential IDs (Student1, Student2, ...) were generated. Use id= parameter to specify the ID column explicitly.
#> No ID column detected. All columns treated as response data. Sequential IDs (Student1, Student2, ...) were generated. Use id= parameter to specify the ID column explicitly.
#> 
iter 1 LogLik -3960.28                                                          
#> 
iter 2 LogLik -3938.35                                                          
#> 
iter 3 LogLik -3931.82                                                          
#> 
iter 4 LogLik -3928.68                                                          
#> 
iter 5 LogLik -3926.99                                                          
#> 
iter 6 LogLik -3926.05                                                          
#> 
iter 7 LogLik -3925.51                                                          
#> 
iter 8 LogLik -3925.19                                                          
#> 
iter 9 LogLik -3925.01                                                          
#> 
iter 10 LogLik -3924.9                                                          
#> 
iter 11 LogLik -3924.83                                                         
#> 
iter 12 LogLik -3924.8                                                          
#> 
iter 13 LogLik -3924.77                                                         
plotIIC_overlay_gg(result_irt) # All items

plotIIC_overlay_gg(result_irt, items = 1:5) # First 5 items only


# GRM example
result_grm <- GRM(J5S1000)
#> Parameters: 18 | Initial LL: -6252.352 
#> initial  value 6252.351598 
#> iter  10 value 6032.463982
#> iter  20 value 6010.861094
#> final  value 6008.297278 
#> converged
plotIIC_overlay_gg(result_grm, show_legend = TRUE)

# }