plotICC {eRm} | R Documentation |
Various plot functions for visualizing the item characteristic curves
## S3 method for class 'Rm': plotICC(object, item.subset = "all", empirical = FALSE, xlim = c(-4, 4), ylim = c(0, 1), xlab = "Latent Dimension", ylab = "Probability to Solve", ...) ## S3 method for class 'dRm': plotjointICC(object, item.subset = "all", legend = TRUE, xlim = c(-4, 4), ylim = c(0, 1), xlab = "Latent Dimension", ylab = "Probability to Solve", lty = 1, ...)
object |
object of class Rm or dRm |
item.subset |
Subset of items to be plotted. Either a numeric vector indicating
the column in X or a character vector indiciating the column name.
If "all" , all items are plotted. |
empirical |
Option for plotting the empirical ICCs for objects of class dRm |
legend |
If TRUE , legend is provided, otherwise the ICCs are labeled. |
xlab |
Label of the x-axis. |
ylab |
Label of the y-axis. |
xlim |
Range of person parameters. |
ylim |
Range for probability to solve. |
lty |
Line type. |
... |
Additional plot parameters. |
Patrick Mair, Reinhold Hatzinger
# Rating scale model, ICC plot for all items data(rsmdat) res <- RSM(rsmdat) plotICC(res) # Rasch model with empirical ICCs newdata <- matrix(sample(0:1, 1000, replace = TRUE), ncol = 5) res <- RM(newdata) plotICC(res, empirical = TRUE) # Joint ICC plot for items 2, 6, 8, and 15 for a Rasch model data(raschdat1) res <- RM(raschdat1) plotjointICC(res, item.subset = c(2,6,8,15))