I have built an GPCM IRT model using survey data, but have found significant local dependence (in violation of the LID assumption) using residuals()
in R
. I've found information online for dealing with LD in Rasch models-- you can combine them into "super-items", which makes them polytomous.
Can I do this with polytomous data? What exactly does this mean (is it an item with no question and 10 response categories)?
Finally, how do you know which items to combine? Unfortunately, nearly all of my items are scoring high with more than one other item. I did use EFA (and MIRT) to see whether perhaps I was missing a dimension, but I can't seem to find anything significant.