plotDIFirt {ShinyItemAnalysis}

Plot item characteristic curve of DIF IRT model

Description

Plots characteristic curve of IRT model.

Usage

plotDIFirt(
  parameters,
  test = "Lord",
  item = "all",
  item.name,
  same.scale = FALSE
)

Arguments

parameters

numeric: data matrix or data frame. See Details.

test

character: type of statistic to be shown. See Details.

item

either character ("all"), or numeric vector, or single number corresponding to column indicators. See Details.

item.name

character: the name of item.

same.scale

logical: are the item parameters on the same scale? (default is "FALSE"). See Details.

Details

This function plots characteristic curve of DIF IRT model.

The parameters matrix has a number of rows equal to twice the number of items in the data set. The first J rows refer to the item parameter estimates in the reference group, while the last J ones correspond to the same items in the focal group. The number of columns depends on the selected IRT model: 2 for the 1PL model, 5 for the 2PL model, 6 for the constrained 3PL model and 9 for the unconstrained 3PL model. The columns of irtParam() have to follow the same structure as the output of itemParEst(), difLord() or difRaju() command from the difR package.

Two possible type of test statistics can be visualized - "Lord" gives only characteristic curves, "Raju" also highlights area between these curves.

For default option "all", all characteristic curves are plotted.

Author(s)

Adela Hladka
Institute of Computer Science of the Czech Academy of Sciences
[e-mail]

Patricia Martinkova
Institute of Computer Science of the Czech Academy of Sciences
[e-mail]

See Also

difR::itemParEst(), difR::difLord(), difR::difRaju()

Examples

# loading libraries
library(difR)
library(ltm)

# loading data based on GMAT2
data(GMAT2, package = "difNLR")

# Estimation of 2PL IRT model and Lord's statistic
# by difR package
fitLord <- difLord(GMAT2, group = 21, focal.name = 1, model = "2PL")
# plot of item 1 and Lord's statistic
plotDIFirt(fitLord$itemParInit, item = 1)

# Estimation of 2PL IRT model and Raju's statistic
# by difR package
fitRaju <- difRaju(GMAT2, group = 21, focal.name = 1, model = "2PL")
# plot of item 1 and Lord's statistic
plotDIFirt(fitRaju$itemParInit, test = "Raju", item = 1)