View source: R/model-criticism.R
| cross_sectional_learning | R Documentation |
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")
)
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 |
numeric vector of learning scores (post - pre)
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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.