Hi Jeanette,
The packages use different parameterizations for the models, so direct
comparison between them would require a little math to determine the
link for partial credit models. For instance, we can compare the Rasch
models between the packages like so:
library(eRm)
library(mirt)
dat <- expand.table(LSAT7)
res <- RM(dat)
cfs <- coef(res)
scale(cfs)
#for 'Rasch', fix the slopes = 1, estimate all the b's and latent
variance parameter
mres <- mirt(dat, 1, itemtype= 'Rasch')
cfs <- coef(mres, IRTpars = TRUE)
b <- numeric(5)
for(i in 1:5) b[i] <- cfs[[i]][2L]
scale(b)
You'll notice that you have to rescale the results of the intercepts
to put them onto the same metric. They also won't be exactly the same
since eRm uses CML estimation while mirt uses MML.
Phil
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