Currently I'm working on a project in which I use Item response theory. I have 8 variables from a lot of cases, which I would like to find the latent variable for. Now, the problem is that there is quite some missing data. I already worked out how to impute some of the values, but now I want to make another model, in which I drop all the observations which have missing values for more than 4 of the 8 variables, because imputing these can be seen as inreliable. I've looked around in multiple manuals, but can't seem to find what I'm looking for.