expected.test: Function to calculate expected test score

In mirt: Multidimensional Item Response Theory

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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v048.i06")}

See Also

expected.item

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)

mirt documentation built on Sept. 11, 2024, 7:14 p.m.