Hi everyone, I’m looking for some advice.
I am a political scientist and am doing some research on democracy. I have 11 different dichotomous measures of democracy, each of which takes the value 0 if some country in some year was non-democratic and 1 if it was. I’d like to fit a 2 parameter IRT model to these data. The problem, however, is that the measures are not independent, since some draw on others for inspiration/to corroborate unfamiliar cases. As such, there is a risk of double-counting cases.
To my mind, this is akin to the problem that phylogenetic regression tries to solve, except here the relationship between my measures is more ambiguous (and it’s not like I can test their DNA). Nevertheless, can I simply compute the measures’ covariance matrix and pass this to the
cov = argument in the
gr() function to account for the relationship between the measures? Or is there something more sophisticated that I need to do to account for this?