regionplot(object, parg = list(type = NULL, ref = NULL, alias = TRUE), names = TRUE, main = NULL, xlab = "", ylab = "Latent trait", ylim = NULL, off = 0.1, col = NULL, linecol = 2, srt = 45, adj = c(1.1, 1.1), axes = TRUE, ...)
"raschmodel"
, "rsmodel"
or "pcmodel"
.TRUE
, the names of
the items are displayed on the x-axis. If FALSE
, numbers of
items are shown. Alternatively a character vector of the same
length as the number of items can be supplied.gray.colors
, which
is then directly used to create the color names.srt
) and adjustment (adj
)
in case names (rather than numbers) are used as x-axis labels.
These are passed to text
.plot
type
is set to "modus"
, the
cutpoints correspond to the threshold parameters and the rectangles
mark the theta regions where a category is the single most probable
category chosen with a certain value of the latent trait. If
type
is set to "median"
, the cutpoints correspond to the
point on the theta axis, where the cumulative probability to score in
category $k$ or higher is 0.5, i.e., $P(X_{ij} \geq k) =
0.5$. If set to "mean"
, the cutpoints correspond to the point
on the theta axis where the expected score $E(X_{ij})$ is
exactly between two categories, e.g., 0.5 for a dichotomous item. If type
is set to "mode"
and there are unordered
threshold parameters, the location of the original threshold
parameters are indicated by red dashed lines.
R
for Multinomial and Proportional-Odds Logit Models: Extensions to the
effects Package. Journal of Statistical Software, 32(1),
http://www.jstatsoft.org/v32/i01/Van der Linden, W. J. & Hambleton, R. K. (1997). Handbook of Modern Item Response Theory. Springer, New York.
curveplot
, profileplot
,
infoplot
, piplot
## Load Verbal aggression data
data("VerbalAggression", package = "psychotools")
## Fit a Partial credit model to the items of the
## first other-to-blame situation: 'A bus fails to stop for me'
pcm <- pcmodel(VerbalAggression$resp[, 1:6])
## A region plot with modus as cutpoint and custom labels.
lab <- paste(rep(c("Curse", "Scold", "Shout"), each = 2),
rep(c("Want", "Do"), 3 ), sep = "-")
plot(pcm, type = "regions", names = lab)
## Compare the cutpoints (with ylim specified manually)
opar <- par(no.readonly = TRUE)
ylim <- c(-2, 2)
layout(matrix(1:3, ncol = 1))
plot(pcm, type = "regions", parg = list(type = "mode"),
main = "Modus as Cutpoint", ylim = ylim)
plot(pcm, type = "regions", parg = list(type = "median"),
main = "Median as Cutpoint", ylim = ylim)
plot(pcm, type = "regions", parg = list(type = "mean"),
main = "Mean as Cutpoint", ylim = ylim)
par(opar)
## Partial credit model for full VerbalAggression data set
pcm_va <- pcmodel(VerbalAggression$resp)
plot(pcm_va, type = "regions")
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