guess_stnderr function

Bootstrapped standard errors of effect size estimates

guess_stnderr

guess_stnderr(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.

Returns

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: guess_stnderr(pre_test, pst_test, nsamps=10, seed = 31415)