gen.difficulty {mirt} | R Documentation |
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.
gen.difficulty(mod, type = "IRF", interval = c(-30, 30), ...)
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 |
Phil Chalmers rphilip.chalmers@gmail.com
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
## 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)