Description Usage Arguments Author(s) References Examples
Given an estimated model compute the test information.
1 2 |
x |
an estimated mirt object |
Theta |
a matrix of latent trait values |
degrees |
a vector of angles in degrees that are between 0 and 90. Only applicable when the input object is multidimensional |
group |
a number signifying which group the item should be extracted from (applies to 'MultipleGroupClass' objects only) |
individual |
logical; return a data.frame of information traceline for each item? |
which.items |
an integer vector indicating which items to include in the expected information function. Default uses all possible items |
Phil Chalmers rphilip.chalmers@gmail.com
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ## Not run:
dat <- expand.table(deAyala)
(mirt(dat, 1, '2PL', pars = 'values'))
mod <- mirt(dat, 1, '2PL', constrain = list(c(1,5,9,13,17)))
Theta <- matrix(seq(-4,4,.01))
tinfo <- testinfo(mod, Theta)
plot(Theta, tinfo, type = 'l')
#compare information loss between two tests
tinfo_smaller <- testinfo(mod, Theta, which.items = 3:5)
#removed item informations
plot(Theta, iteminfo(extract.item(mod, 1), Theta), type = 'l')
plot(Theta, iteminfo(extract.item(mod, 2), Theta), type = 'l')
#most loss of info around -1 when removing items 1 and 2; expected given item info functions
plot(Theta, tinfo_smaller - tinfo, type = 'l')
## End(Not run)
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