Score an item LCA fit on individual responses — score_individual

Evaluates a fitted item-level latent-class model on paired individual responses. The aggregate likelihood equals [score_item_lca()] applied to transition counts made from the same responses.

score_individual_lca(
  fit,
  pre_test,
  post_test,
  ...,
  na_as = c("dk", "missing"),
  missing_action = c("omit", "error")
)

Arguments

fit: A `guess_fit` object returned by [fit_item_lca_counts()] or [fit_item_lca()].
pre_test: Data frame containing one pre-test item per column.
post_test: Data frame containing the corresponding post-test items.
...: Must be empty.
na_as: Classification of `NA` responses: `"dk"` treats them as observed don't-know responses and `"missing"` treats them as structural missingness.
missing_action: How to handle structural missingness: `"omit"` excludes incomplete pairs and `"error"` rejects them.

Value

A `guess_individual_score` object. `individual_scores` contains one row per respondent; rows with no observed item pairs have `NA` mean score and perplexity. Aggregate fields are observation-weighted across all observed item pairs.