transmat: transmat: Cross-wave transition matrix

In soodoku/guess: Adjust Estimates of Learning for Guessing

Description

Prints Cross-wave transition matrix and returns the vector behind the matrix. Missing values are treated as ignorance. Don't know responses need to be coded as 'd'.

Usage

transmat(pre_test_var, pst_test_var, subgroup = NULL, force9 = FALSE)

Arguments

pre_test_var	Required. A vector carrying pre-test scores of a particular item. Only
pst_test_var	Required. A vector carrying post-test scores of a particular item
subgroup	Optional. A Boolean vector indicating rows of the relevant subset.
force9	Optional. There are cases where DK data doesn't have DK. But we need the entire matrix. By default it is FALSE.

Value

a numeric vector. Assume 1 denotes correct answer, 0 and NA incorrect, and d 'don't know.' When there is no don't know option and no missing, the entries are: x00, x10, x01, x11 When there is a don't know option, the entries of the vector are: x00, x10, xd0, x01, x11, xd1, xd0, x1d, xdd

Examples

pre_test_var <- c(1,0,0,1,0,1,0)
pst_test_var <- c(1,0,1,1,0,1,1)
transmat(pre_test_var, pst_test_var)

# With NAs
pre_test_var <- c(1,0,0,1,"d","d",0,1,NA)
pst_test_var <- c(1,NA,1,"d",1,0,1,1,"d") 
transmat(pre_test_var, pst_test_var)

soodoku/guess documentation built on Dec. 31, 2021, 5:19 p.m.