Item selection by network distance criterion.

Administers the item farthest in the item network from the items a respondent has already answered, with edges weighted by the inverse of their entry in the item-item adjacency matrix. Ties are broken using the maximum information criterion.

Usage

select_max_dist(pers, item, R, admin, adj_mat = NULL, n_candidates = 1)

Arguments

pers: A data frame of current respondent ability estimates.
item: A data frame of current item parameter estimates.
R: A respondent-by-item matrix of potential responses.
admin: An integer administration matrix; 0 indicates an item has not been administered to a respondent. See meow() for details.
adj_mat: An item-item adjacency matrix. See construct_adj_mat().
n_candidates: The number of farthest items to assemble into a candidate pool before selecting the next item by maximum information. Allows users to trade off network density against estimation efficiency.

Value

An updated administration matrix with the selected item marked for each respondent.

Examples

sim <- meow(select_max_dist, update_theta_mle, data_simple_1pl,
            data_args = list(N_persons = 10, N_items = 10), fix = "item")
nrow(sim$results)
#> [1] 6