Estimate a Cross-Sectional Logit Score

Computes the empirical logit of each person's proportion correct. The denominator-aware half-count correction keeps all-observed scores finite. This is a descriptive score, not a fitted item-response model.

estimate_logit_score(
  responses,
  na_as = c("dk", "missing"),
  missing_action = c("omit", "error")
)

Arguments

responses

data.frame of binary responses (0/1)

na_as

classification of NA responses

missing_action

structural missingness handling

Value

numeric vector of logit scores (length = n individuals)

Details

Observed d/DK responses are scored as incorrect in this binary correctness baseline. They remain a distinct response category in the LCA functions. The empirical-logit correction is from Cox and Snell (1989, Section 2.1.6); respondents with no observed responses receive `NA`.

References

Cox, D. R., and Snell, E. J. (1989). *Analysis of Binary Data* (2nd ed.). Chapman and Hall.

Examples

sim <- simulate_lca(n = 100, seed = 123)
score_pre <- estimate_logit_score(sim$pre)
score_post <- estimate_logit_score(sim$post)