I am running a series of models on the same dataset. I have eight binary manifest variables, one latent variable and twelve groups. I am fixing the means and variances of the manifests and estimating the thresholds. The series of models differ in the following way.
1 - common parameter (lambda) for all manifest variables but separate thresholds (tau - eight values)
2 - common lambda but separate tau for all items in each group (96 taus)
3 - separate lambda for each group (12) and separate tau (96)
4 - separate lambda for each manifest (8) with 8 tau
5 - separate lambda for each manifest (8) with 96 tau
6 - separate lambda for each manifest for each group (96) with 96 tau
I developed and tested the models using only two groups and apart from some code green messages from the optimiser all ran well and I got sensible looking results. However when I run the models on the full dataset only model 1 terminates. I turned on output of checkpoints and I observe that all goes well for a while but then it stops writing to the checkpoint file but does not terminate either. Looking at the last couple of checkpoints it seems that the value of the objective has settled down although the parameter values are not that close. A further irritation is that on my Windows box it also freezes RGui for some reason. On my Linux box it just sits there. The behaviour of stopping writing to the checkpoint file seems the same under both OS.
I can make the scripts available. The dataset is not mine and I would prefer to email it rather than post it openly. But perhaps someone has an idea of what I should try next