Bootstrapped standard errors of effect size estimates

guess_stnderr

lca_se(pre_test = NULL, pst_test = NULL, nsamps = 100, seed = 31415,
  force9 = FALSE)

Arguments

pre_test	data.frame carrying pre_test items
pst_test	data.frame carrying pst_test items
nsamps	number of resamples, default is 100
seed	random seed, default is 31415
force9	Optional. There are cases where DK data doesn't have DK. But we need the entire matrix. By default it is FALSE.

Value

list with standard error of parameters, estimates of learning, 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, nsamps = 10, seed = 31415)
# }