Description Usage Arguments References Examples
Plot various test implied response functions from models estimated in the mirt package.
1 2 3 4 5 6 7 8 9 | ## S4 method for signature 'SingleGroupClass,missing'
plot(x, y, type = "score", npts = 50,
degrees = 45, theta_lim = c(-6, 6), which.items = 1:extract.mirt(x,
"nitems"), MI = 0, CI = 0.95, rot = list(xaxis = -70, yaxis = 30, zaxis
= 10), facet_items = TRUE, main = NULL, drape = TRUE, colorkey = TRUE,
ehist.cut = 1e-10, add.ylab2 = TRUE, par.strip.text = list(cex = 0.7),
par.settings = list(strip.background = list(col = "#9ECAE1"), strip.border =
list(col = "black")), auto.key = list(space = "right"), profile = FALSE,
...)
|
x |
an object of class |
y |
an arbitrary missing argument required for |
type |
type of plot to view. Can be
Note that if |
npts |
number of quadrature points to be used for plotting features. Larger values make plots look smoother |
degrees |
numeric value ranging from 0 to 90 used in |
theta_lim |
lower and upper limits of the latent trait (theta) to be evaluated, and is
used in conjunction with |
which.items |
numeric vector indicating which items to be used when plotting. Default is to use all available items |
MI |
a single number indicating how many imputations to draw to form bootstrapped confidence intervals for the selected test statistic. If greater than 0 a plot will be drawn with a shaded region for the interval |
CI |
a number from 0 to 1 indicating the confidence interval to select when MI input is used. Default uses the 95% confidence (CI = .95) |
rot |
allows rotation of the 3D graphics |
facet_items |
logical; apply grid of plots across items? If |
main |
argument passed to lattice. Default generated automatically |
drape |
logical argument passed to lattice. Default generated automatically |
colorkey |
logical argument passed to lattice. Default generated automatically |
ehist.cut |
a probability value indicating a threshold for excluding cases in empirical histogram plots. Values larger than the default will include more points in the tails of the plot, potentially squishing the 'meat' of the plot to take up less area than visually desired |
add.ylab2 |
logical argument passed to lattice. Default generated automatically |
par.strip.text |
plotting argument passed to |
par.settings |
plotting argument passed to |
auto.key |
plotting argument passed to |
profile |
logical; provide a profile plot of response probabilities (objects returned from
|
... |
additional arguments to be passed to lattice |
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi: 10.18637/jss.v048.i06
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | ## Not run:
x <- mirt(Science, 1, SE=TRUE)
plot(x)
plot(x, type = 'info')
plot(x, type = 'infotrace')
plot(x, type = 'infotrace', facet_items = FALSE)
plot(x, type = 'infoSE')
plot(x, type = 'rxx')
# confidence interval plots when information matrix computed
plot(x)
plot(x, MI=100)
plot(x, type='info', MI=100)
plot(x, type='SE', MI=100)
plot(x, type='rxx', MI=100)
# use the directlabels package to put labels on tracelines
library(directlabels)
plt <- plot(x, type = 'trace')
direct.label(plt, 'top.points')
set.seed(1234)
group <- sample(c('g1','g2'), nrow(Science), TRUE)
x2 <- multipleGroup(Science, 1, group)
plot(x2)
plot(x2, type = 'trace')
plot(x2, type = 'trace', which.items = 1:2)
plot(x2, type = 'trace', which.items = 1, facet_items = FALSE) #facet by group
plot(x2, type = 'info')
x3 <- mirt(Science, 2)
plot(x3, type = 'info')
plot(x3, type = 'SE', theta_lim = c(-3,3))
## End(Not run)
|
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