expected.test: Function to calculate expected test score

In xzhaopsy/MIRT: Multidimensional Item Response Theory

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)

Arguments

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

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

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))


## End(Not run)

xzhaopsy/MIRT documentation built on May 29, 2019, 12:42 p.m.