Cross-sectional learning estimate

Estimates learning as the difference in logit scores between post and pre. This ignores the transition structure that the LCA model uses.

cross_sectional_learning(
  pre_test,
  pst_test,
  na_as = c("dk", "missing"),
  missing_action = c("omit", "error")
)

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

Value

numeric vector of learning scores (post - pre)

Examples

sim <- simulate_lca(n = 100, gk = 0.30, seed = 123, return_classes = TRUE)
learning_cs <- cross_sectional_learning(sim$pre, sim$post)
cor(learning_cs, sim$learned)
#> [1] 0.7188261