Plot threshold probability curves

Conditional probability of success at each threshold, P(X = k | X = k - 1 or k), a logistic ogive crossing 0.5 at the threshold location. Disordered thresholds are immediately visible as out-of-sequence ogives. With observed = TRUE the observed conditional proportions per class interval are overlaid, the direct check on whether each threshold discriminates (and hence whether collapsing categories could ever be justified; Andrich and Marais 2019, ch. 22).

Usage

plot_threshold_prob(fit, item, grid = NULL, observed = FALSE, n_groups = NULL)

Arguments

fit

A fitted object from rasch.

item

Item name or column index.

grid

Logit grid over which to draw the curves.

observed

Overlay the observed conditional threshold proportions per class interval.

n_groups

Class intervals for the observed points; by default the fit's own allocation for this item, so the points match the item-trait test they illustrate.

Value

Called for its plotting side effect; invisibly NULL.

Examples

set.seed(1)
simP <- function(th, t) { x <- 0:length(t); p <- exp(x * th - c(0, cumsum(t))); p / sum(p) }
th <- rnorm(400)
X <- sapply(1:4, function(i)
  sapply(th, function(t)
    sample(0:3, 1, prob = simP(t, c(-1, 0, 1)))))
colnames(X) <- sprintf("P%02d", 1:4)
plot_threshold_prob(rasch(X), "P01")