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Plot Item Characteristic Curves (ICC) from exametrika

Source: R/ICCtoTIC.R
plotICC_gg.Rd

This function takes exametrika IRT output as input and generates Item Characteristic Curves (ICC) using ggplot2. ICC shows the probability of a correct response as a function of ability (theta).

Usage

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

Arguments

data

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

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 (only for single-item plots).

colors

Character vector. Color(s) for the curve. If NULL (default), a colorblind-friendly palette is used.

linetype

Character or numeric specifying the line type. Default is "solid".

show_legend

Logical. If TRUE, display the legend. Default is FALSE.

legend_position

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

Value

A list of ggplot objects, one for each item. Each plot shows the Item Characteristic Curve for that item.

Details

The function supports 2PL, 3PL, and 4PL IRT models:

  • 2PL: slope (a) and location (b) parameters

  • 3PL: adds lower asymptote (c) parameter

  • 4PL: adds upper asymptote (d) parameter

The ICC is computed using the four-parameter logistic model: $$P(\theta) = c + \frac{d - c}{1 + \exp(-a(\theta - b))}$$

See also

plotIIC_gg, plotTIC_gg

Examples

library(exametrika)
result <- 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                                                         
plots <- plotICC_gg(result)
plots[[1]] # Show ICC for the first item

combinePlots_gg(plots, selectPlots = 1:6) # Show first 6 items