plotICC: Plot item characteristic curves (ICCs)

In GGUM: Generalized Graded Unfolding Model

Plot item characteristic curves (ICCs)

Description

plot.ICC plots the ICCs for the GUM and the GGUM.

Usage

plotICC(IP, Th, items = NULL, quiet = FALSE)

Arguments

IP	Object of class GGUM.
Th	Theta estimates from function Theta.EAP().
items	Vector indicating the items for which the ICCs are to be plotted. Default is all items.
quiet	Render all plots for items at once? Default is FALSE.

Value

The function returns the correlation between observed and expected item scores (missing values pairwise removed).

Details

This function plots the item characteristic curves (ICCs).

Author(s)

Jorge N. Tendeiro, [e-mail]

Examples

## Not run: 
# For GUM:
# Generate data
#   (toy example: Too few items (due to computation time constraints) for 
#   accurate estimation of person parameters; larger number of items is 
#   required in practice):
gen1 <- GenData.GGUM(400, 5, 3, "GUM", seed = 139)
# Fit the GUM:
fit1 <- GUM(gen1$data, 3)
th1  <- Theta.EAP(fit1)
# Plot ICCs:
plotICC(fit1, th1, items = 1, quiet = TRUE)

## End(Not run)
## Not run: 
# For GGUM:
# Generate data:
set.seed(1); C <- sample(3:5, 10, replace = TRUE)
gen2 <- GenData.GGUM(2000, 10, C, "GGUM", seed = 156)
# Fit the GGUM:
fit2 <- GGUM(gen2$data, C)
th2  <- Theta.EAP(fit2)
# Plot ICCs:
plotICC(fit2, th2, items = 1, quiet = TRUE)

## End(Not run)

GGUM documentation built on Sept. 8, 2023, 5:38 p.m.