plotDIFLogistic: Function for characteristic curve of 2PL logistic DIF model
In kitdouble/ShinyIRT: Test and Item Analysis via Shiny

Description Usage Arguments Details Author(s) Examples

Plots characteristic curve of 2PL logistic DIF model

1 2	plotDIFLogistic(data, group, type = "both", item, item.name, IRT = F, p.adjust.method = "none", purify = F)

`data`	numeric: the data matrix. See Details.
`group`	numeric: the vector of group membership. See Details.
`type`	character: a character string specifying which DIF effects must be tested. Possible values are "both" (default), "udif" and "nudif". See Details.
`item`	numeric: number of item to be plotted
`item.name`	character: the name of item.
`IRT`	logical: if IRT parameterization (`TRUE`, default) or classic logistic parameterization (`FALSE`) may be applied.
`p.adjust.method`	character: the acronym of the method for p-value adjustment for multiple comparisons. See Details.
`purify`	logical: if item purification may be applied.

This function plots characteristic curve of 2PL logistic DIF model.

Adela Drabinova
Institute of Computer Science, The Czech Academy of Sciences
Faculty of Mathematics and Physics, Charles University
drabinova@cs.cas.cz

Patricia Martinkova
Institute of Computer Science, The Czech Academy of Sciences
martinkova@cs.cas.cz

## Not run: 
# loading libraries
library(difNLR, difR)

 # loading data based on GMAT
data(GMAT, package = "difNLR")
data  <- GMAT[, colnames(GMAT) != "group"]
group <- GMAT[, "group"]

# Characteristic curve by logistic regression model
plotDIFLogistic(data, group, item = 1)

# Characteristic curve by logistic regression model using scaled score
plotDIFLogistic(data, group, item = 1, IRT = T)

## End(Not run)