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Hi Diego,
I think you are best transforming your data into long format and fitting a cross-classified model with exam score nested within pupil and school. That way you can easily include time varying covariates as you have 1 response per year. The alternative/extension where you make the school ...

Dear DrDTorres,
My main concern here is whether your response is 1 per year ? If so then you simply have a simple 3 level model. If you want to do something more complicated then
as I see it you have several choices. You could fit a variant of a cross-classified model which is in fact a 3 level ...

Dear mwkoeter,
The intervals and tests window under Estimation will do this. You simply choose the fixed button at the bottom of the screen and increase # of functions to 3. Then for each column place a 1 next to 1 of the 3 dummies ( a different one for each column) and click calc to get the chi ...

Dear user,
I'll be honest with you and say that I am not sure I have ever tried a binary response model with spatial random effects. The majority of the time in disease mapping which is the field for which I coded the CAR modelling section the responses are treated as counts and fitted as Poisson ...

Dear medha001,
Just last week we came across a similar issue. The problem is if you have individuals who are missing on all responses then this causes issues with MLwiN when you switch to MCMC. We have made a change that will fix these issues, which will appear in the next version 2.27 but strictly ...

Hi,
In the situation in which you have level 1 variables that you make random at level 2 and for some reason IGLS gives a non-positive definite answer then the advice is to change the values prior to running MCMC so that they make sense. The values you choose have 2 roles - (i) starting values for ...

There is no theory based fixed difference e.g. 10 that should be compared when comparing the DIC of two models although 10 might have been a rule of thumb suggested by someone - in theory the model with the lowest DIC is better but of course there is stochastic noise when using MCMC so a very small ...

Dear hdilk0507,
I saw your question and have a quick answer. It really makes no sense to allow a level 2 variable to vary across level 2 units. Consider 1 level 2 unit then the predictor associated with the intercept will take value 1 for all individuals in the unit and the level 2 variable will ...

Hi Econsic1976,
This is because the residuals are shrunken residuals - I think the answer might be quite technical and available in Harvey Goldstein's book or you could email him.
Regards,
Bill.

Hi Mdommers,
I could take a look if you send me your worksheet (william.browne@bristol.ac.uk).
Regards,
Bill.