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\name{curveplot}
\alias{curveplot}
\title{Response Curve Plots for IRT Models}
\description{
Base graphics plotting function for response curve plot visualization of IRT
models.
}
\usage{
curveplot(object, ref = NULL, items = NULL, names = NULL,
layout = NULL, xlim = NULL, ylim = c(0, 1), col = NULL,
lty = NULL, main = NULL, xlab = "Latent trait",
ylab = "Probability", add = FALSE, \dots)
}
\arguments{
\item{object}{a fitted model object of class \code{"raschmodel"},
\code{"rsmodel"}, \code{"pcmodel"}, \code{"plmodel"} or \code{"gpcmodel"}.}
\item{ref}{argument passed over to internal calls of \code{\link{predict}}.}
\item{items}{character or numeric, specifying the items for which response
curves should be visualized.}
\item{names}{character, specifying labels for the items.}
\item{layout}{matrix, specifying how the response curve plots of different
items should be arranged.}
\item{xlim, ylim}{numeric, specifying the x and y axis limits.}
\item{col}{character, specifying the colors of the response curve lines. The
length of \code{col} should be the maximum number of available categories.}
\item{lty}{numeric, specifying the line type of the response curve lines. The
length of \code{lty} should either be one or the maximum number of
available categories. In the first case, a single line type is used for all
category response curves. In the latter case, separate line types for each
category response curve are used.}
\item{main}{character, specifying the overall title of the plot.}
\item{xlab, ylab}{character, specifying the x and y axis labels.}
\item{add}{logical. If \code{TRUE}, new response curves are added to an
existing plot. Only possible when a single item is visualized.}
\item{\dots}{further arguments passed to internal calls of
\code{\link{matplot}}.}
}
\details{
The response curve plot visualization illustrates the predicted probabilities
as a function of the ability parameter \eqn{\theta} under a certain IRT model.
This type of visualization is sometimes also called item/category operating
curves or item/category characteristic curves.
}
\seealso{\code{\link{regionplot}}, \code{\link{profileplot}},
\code{\link{infoplot}}, \code{\link{piplot}}}
\examples{
## load verbal aggression data
data("VerbalAggression", package = "psychotools")
## fit Rasch, rating scale and partial credit model to verbal aggression data
rmmod <- raschmodel(VerbalAggression$resp2)
rsmod <- rsmodel(VerbalAggression$resp)
pcmod <- pcmodel(VerbalAggression$resp)
## curve plots of the dichotomous RM
plot(rmmod, type = "curves")
## curve plots under the RSM for the first six items of the data set
plot(rsmod, type = "curves", items = 1:6)
## curve plots under the PCM for the first six items of the data set with
## custom labels
plot(pcmod, type = "curves", items = 1:6, names = paste("Item", 1:6))
## compare the predicted probabilities under the RSM and the PCM for a single
## item
plot(rsmod, type = "curves", item = 1)
plot(pcmod, type = "curves", item = 1, lty = 2, add = TRUE)
legend(x = "topleft", y = 1.0, legend = c("RSM", "PCM"), lty = 1:2, bty = "n")
\donttest{
if(requireNamespace("mirt")) {
## fit 2PL and generaliced partial credit model to verbal aggression data
twoplmod <- plmodel(VerbalAggression$resp2)
gpcmod <- gpcmodel(VerbalAggression$resp)
## curve plots of the dichotomous 2PL
plot(twoplmod, type = "curves", xlim = c(-6, 6))
## curve plots under the GPCM for the first six items of the data set
plot(gpcmod, type = "curves", items = 1:6, xlim = c(-6, 6))
}
}
}
\keyword{aplot}
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