ShinyItemAnalysis (version 1.5.4)

plotDIFLogistic: Function for characteristic curve of 2PL logistic DIF model

Description

Plots characteristic curve of 2PL logistic DIF model

Usage

plotDIFLogistic(x, item = 1, item.name, group.names = c("Reference",
  "Focal"), Data, group, match, draw.empirical = TRUE)

Arguments

x

an object of "Logistic" class. See Details.

item

numeric: number of item to be plotted

item.name

character: the name of item to be used as title of plot.

group.names

character: names of reference and focal group.

Data

numeric: the data matrix. See Details.

group

numeric: the vector of group membership. See Details.

match

character or numeric: specifies observed score used for matching. Can be either "score", or numeric vector of the same length as number of observations in Data. See Details.

draw.empirical

logical: whether empirical probabilities should be calculated and plotted. Default value is TRUE.

Author

Adela Hladka
Institute of Computer Science of the Czech Academy of Sciences

Patricia Martinkova
Institute of Computer Science of the Czech Academy of Sciences

Details

This function plots characteristic curves of 2PL logistic DIF model fitted by difLogistic() function from difR package using ggplot2.

Data and group are used to calculate empirical probabilities for reference and focal group. match should be the same as in x$match. In case that an observed score is used as a matching variable instead of the total score or the standardized score, match needs to be a numeric vector of the same the same length as the number of observations in Data.

See Also

difR::difLogistic(), ggplot2::ggplot()

Examples

# loading libraries
library(difR)

# loading data based on GMAT
data(GMAT, package = "difNLR")
Data <- GMAT[, 1:20]
group <- GMAT[, 21]

# DIF detection using difLogistic() function
x <- difLogistic(Data, group, focal.name = 1)
# Characteristic curve by logistic regression model
plotDIFLogistic(x, item = 1, Data = Data, group = group)

# Using name of column as item identifier
plotDIFLogistic(x, item = "Item1", Data = Data, group = group)

# Renaming reference and focal group
plotDIFLogistic(x, item = 1, group.names = c("Group 1", "Group 2"), Data = Data, group = group)

# Not plotting empirical probabilities
plotDIFLogistic(x, item = 1, draw.empirical = FALSE)