person_item_lca_fit: Fit a Joint Person-Level Latent Class Model

In guess: Adjust Estimates of Learning for Guessing

Fit a Joint Person-Level Latent Class Model

Description

Fits one latent transition class per person across repeated items. Class proportions are shared across items, while guessing probabilities are item-specific. Parameters are estimated jointly by expectation-maximization.

Usage

person_item_lca_fit(
  pre_test,
  pst_test,
  na_as = c("dk", "missing"),
  missing_action = c("omit", "error"),
  item_fit = NULL,
  max_iter = 1000L,
  tol = 1e-08
)

Arguments

pre_test	data frame of pre-test responses
pst_test	data frame of post-test responses
na_as	classification of NA responses
missing_action	structural missingness handling
item_fit	optional item-wise fit used to initialize the EM algorithm
max_iter	maximum EM iterations
tol	convergence tolerance

Details

This is distinct from item_lca_fit, which fits independent class proportions for each item.

Value

An object of class guess_person_fit containing shared class proportions, item-specific guessing probabilities, person-level posterior probabilities, log-likelihood, and convergence information.

Examples

sim <- simulate_lca(n = 500, n_items = 4, seed = 123)
fit <- person_item_lca_fit(sim$pre, sim$post)
fit$class_priors
head(fit$posterior)

guess documentation built on Aug. 3, 2026, 9:07 a.m.