Function to calculate expected test score
Given an estimated model compute the expected test score. Returns the expected values in the same form as the data used to estimate the model.
expected.test( x, Theta, group = NULL, mins = TRUE, individual = FALSE, which.items = NULL )
x |
an estimated mirt object |
Theta |
a matrix of latent trait values |
group |
a number signifying which group the item should be extracted from (applies to 'MultipleGroupClass' objects only) |
mins |
logical; include the minimum value constants in the dataset. If FALSE, the expected values for each item are determined from the scoring 0:(ncat-1) |
individual |
logical; return tracelines for individual items? |
which.items |
an integer vector indicating which items to include in the expected test score. Default uses all possible items |
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi: 10.18637/jss.v048.i06
## Not run: dat <- expand.table(deAyala) model <- 'F = 1-5 CONSTRAIN = (1-5, a1)' mod <- mirt(dat, model) Theta <- matrix(seq(-6,6,.01)) tscore <- expected.test(mod, Theta) tail(cbind(Theta, tscore)) # use only first two items (i.e., a bundle) bscore <- expected.test(mod, Theta, which.items = 1:2) tail(cbind(Theta, bscore)) ## End(Not run)
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