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Ok great, many thanks for the confirmation.

I have been experimenting with creating models using sets of constraints for both the fixed and random effects parameters, but have encountered some difficulty in working out how exactly these are incorporated into the procedures used for parameter estimation in MLwiN (using IGLS). Would anyone be ...

Does anyone have any thoughts or suggestions on this? I can give more model and/or error message details if that would help? I'm still having trouble finding any useful guidance on this issue.

Many thanks

Oliver

Thank you for the follow-up. I was initially thinking that this problem would require something more complicated than adding up the variance function at each level (I'm still getting started on this type of modelling). However, I had just about come around to the conclusion that this method (i.e ...

I am trying to fit longitudinal growth models with measurement occasion at level 1 and individual subject at level 2. The time points in the dataset are unbalanced, with different numbers of measurement occasions and variable time points for each individual included. My problem is that the level 1 ...

Thank you for the reply, that's very helpful. As I understand it, the variance function window only gives the variance for a single level of the model at a time, whereas I am looking to create a summary of the variance across all levels of the model. As such, I think that I may need to use the model ...

I am creating a longitudinal growth model in which a biometric variable at time 't' (level 1) is modeled as a polynomial function of the age of the individual. The data relates to twins, and so each individual (level 2) is furthermore nested within another set (level 3). I have created models with ...