update_theta_mle: Update person ability via maximum likelihood estimation.

In meow: Unified Framework for Computer Adaptive Testing Simulations

Update person ability via maximum likelihood estimation.

Description

This update function treats item parameters as fixed and known and updates person ability estimates after each iteration with a maximum likelihood estimate based on a 2PL item response function.

Usage

update_theta_mle(pers, item, R, admin)

Arguments

pers	A data frame of current respondent parameter estimates.
item	A data frame of item parameter values.
R	A respondent-by-item matrix of potential responses.
admin	An integer administration matrix; non-zero entries indicate administered items. See meow() for details.

Value

A list with two entries: pers, a data frame with updated respondent ability estimates, and item, the unchanged data frame of item parameters.

Examples

data <- data_simple_1pl(N_persons = 10, N_items = 10)
admin <- matrix(0L, 10, 10)
admin[, 1:5] <- 1L
R <- matrix(data$resp$resp, nrow = 10, byrow = TRUE)
upd <- update_theta_mle(data$pers_tru, data$item_tru, R, admin)
head(upd$pers)

meow documentation built on July 6, 2026, 5:11 p.m.