Plot an object characteristic curve

Plots the expected response for one object against opponent location, with the observed mean response against each sufficiently observed opponent. For dichotomous fits the curve is the win probability; for ordered fits it is the expected response. With fitted position or history effects, model values are weighted means of the fitted expectations for each observed opponent, joined in location order. Judge-group overlays use each group's own comparison context.

Usage

plot_btl_icc(fit, object, group = NULL, grid = NULL, min_n = 10)

Arguments

fit

An object from btl.

object

Object name.

group

Optional judge grouping for a DIF overlay: either one value per comparison row of fit$comparisons or a vector named by every judge in the fit. Observed means are then drawn separately per group, as plot_icc draws person groups.

grid

Opponent-location grid, in logits.

min_n

An opponent's observed point is drawn only when the object (or, in the grouped display, that judge group) met it at least this many times; sparser pairs from incomplete or unbalanced designs are omitted.

Value

Called for its plotting side effect; invisibly the names of the opponents drawn (the ungrouped display), or NULL for the grouped display.

Examples

set.seed(1)
beta <- c(A = -1, B = -0.3, C = 0.4, D = 0.9)
pr <- t(combn(names(beta), 2))
d <- data.frame(a = rep(pr[, 1], each = 30), b = rep(pr[, 2], each = 30))
p <- plogis(beta[d$a] - beta[d$b])
d$win <- ifelse(runif(nrow(d)) < p, d$a, d$b)
plot_btl_icc(btl(d, "a", "b", winner = "win"), "C")