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Hi Manny,
Apologies half asleep when I wrote the earlier reply and read your code too quickly. The u terms in your model are simply higher level terms and so they are fine and clustering here is fine. The question is really whether one can construct a correlation between the 2 responses at level 1 ...

Hi MannyGomez,
There is a reason why we haven't implemented bivariate mixtures in the MLwiN -> BUGS interface. Basically BUGS struggles with covariance matrices that have constraints in them - in the case of the model you have one variance is constrained to 1 and what you have done in this part of ...

Hi Nils,
Lots of questions so here are some pointers:
1) Orthogonal reparameterization is in theory only of use when MLwiN has to use Metropolis Hastings i.e. when we don't have normal responses and it improves mixing as it gets around the correlations between the various fixed effects. If MLwiN ...

Hi,
I am not sure what is happening here but I'd be happy to take a look at your spreadsheet. I am presuming that your grouping is not a level 5 variable as this would cause issues? Otherwise if you have coded your dummies correctly it shouldn't matter which is used and they should have the same ...

Hi Nils,
Have been discussing your emails with Chris and we will look at why the starting values cause a crash and get back to you. It may be that your starting values are generating an initial position for the variance function which implies a negative variance for certain observations which would ...

Depends what you mean here. Are you using ordered or unordered categories? Would suggest you read the manual chapters on ordered/unordered models in the MLwiN manual and see if this answers your question. The fact that
your data is repeated measures is probably irrelevant here. Bill.

Good Morning Claudia,
It is as you have surmised possible for the IGLS method that really works on the full covariance matrix of the observations to construct parameter estimates that when evaluated as for example between school variances, correlations etc. give implausible values for this ...

Hi bgawarammana,
To add to the last reply. Having spoken to colleagues this comment was made in quite an old version of the manual and has persisted. The main issue with
repeated measures binary data is the assumption of normality for the individual random effects is often not satisfied by the data ...

Hi bgawarammana,

It is possible to fit multilevel binary/categorical response models to data that have a structure of repeated measures within individuals. However just
like all repeated measures models the assumption is that the correlation between individual data points is equal and doesn't ...

Hi Sinavera,
MLwiN only calculates the deviance (-2LL) though generally BIC is a simple formula involving this quantity and the number of parameters in the model and number of observations in the dataset. Things are not quite as simple in multilevel models as there is some disagreement onto what ...