lca_se: Bootstrapped standard errors of effect size estimates

In guess: Adjust Estimates of Learning for Guessing

Bootstrapped standard errors of effect size estimates

Description

Bootstrapped Standard Errors

Usage

lca_se(
  pre_test = NULL,
  pst_test = NULL,
  n_resamples = 100,
  seed = 31415,
  force9 = FALSE,
  na_as = c("dk", "missing"),
  missing_action = c("omit", "error")
)

Arguments

pre_test	data.frame carrying pre_test items
pst_test	data.frame carrying pst_test items
n_resamples	number of resamples, default is 100
seed	random seed, default is 31415
force9	Optional. Force 9-column format even if no DK responses. Default is FALSE.
na_as	Classification of NA responses: '"dk"' (the default) treats them as observed don't know responses; '"missing"' treats them as structural missingness.
missing_action	How to handle structural missingness: '"omit"' excludes incomplete pairs and '"error"' rejects them.

Value

list with:

se_params	standard errors of parameters by item
avg_effects	mean learning estimates
se_effects	standard error of learning by item

Examples

pre_test <- data.frame(pre_item1 = c(1, 0, 0, 1, 0), pre_item2 = c(1, NA, 0, 1, 0))
pst_test <- data.frame(
  pst_item1 = pre_test[, 1] + c(0, 1, 1, 0, 0),
  pst_item2 = pre_test[, 2] + c(0, 1, 0, 0, 1)
)
## Not run: 
lca_se(pre_test, pst_test, n_resamples = 10, seed = 31415)

## End(Not run)

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