expected.test {mirt} | R Documentation |
Function to calculate expected test score
Description
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.
Usage
expected.test(
x,
Theta,
group = NULL,
mins = TRUE,
individual = FALSE,
which.items = NULL,
probs.only = FALSE
)
Arguments
x |
an estimated mirt object |
Theta |
a matrix of latent trait values (if a vector is supplied, will be coerced to a matrix with one column) |
group |
a number or character 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 |
probs.only |
logical; return the probability for each category instead of
traceline score functions? Only useful when |
References
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
See Also
Examples
## 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))
# more low-level output (score and probabilty elements)
expected.test(mod, Theta, individual=TRUE)
expected.test(mod, Theta, individual=TRUE, probs.only=TRUE)
## End(Not run)