mirt (version 1.42)

expected.test: 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 individual=TRUE

References

Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. tools:::Rd_expr_doi("10.18637/jss.v048.i06")

See Also

expected.item

Examples

if (FALSE) {
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)

}