gen.difficulty {mirt} | R Documentation |
Generalized item difficulty summaries
Description
Function provides the four generalized item difficulty representations for polytomous response models described by Ali, Chang, and Anderson (2015). These estimates are used to gauge how difficult a polytomous item may be.
Usage
gen.difficulty(mod, type = "IRF", interval = c(-30, 30), ...)
Arguments
mod |
a single factor model estimated by |
type |
type of generalized difficulty parameter to report.
Can be |
interval |
interval range to search for |
... |
additional arguments to pass to |
Author(s)
Phil Chalmers rphilip.chalmers@gmail.com
References
Ali, U. S., Chang, H.-H., & Anderson, C. J. (2015). Location indices for ordinal polytomous items based on item response theory (Research Report No. RR-15-20). Princeton, NJ: Educational Testing Service. http://dx.doi.org/10.1002/ets2.12065
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
Examples
## Not run:
mod <- mirt(Science, 1)
coef(mod, simplify=TRUE, IRTpars = TRUE)$items
gen.difficulty(mod)
gen.difficulty(mod, type = 'mean')
# also works for dichotomous items (though this is unnecessary)
dat <- expand.table(LSAT7)
mod <- mirt(dat, 1)
coef(mod, simplify=TRUE, IRTpars = TRUE)$items
gen.difficulty(mod)
gen.difficulty(mod, type = 'mean')
## End(Not run)