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Hi Nasirhakimeh,
This is quite unusual data and your question is only a little about multilevel modelling so I'll give a brief answer of what I might do and then leave to see if others have ideas.
So perhaps a straightforward thing to do is to consider each of the 6 types separately e.g. here are ...

HI Nasirihakimeh,
Apologies that I don't fully follow your structure. Do you have people's views nested within places or places nested within people's views? I think the main thing is with only 6 places you are probably looking at fitting fixed effects for these as they are probably important ...

Hi Josip,
You appear to have a 4 level structure but in practice you would fit this as 3-levels with school just included as fixed effect dummies as you only have 4 schools. I am not sure I understand your 2nd question but fitting it as 3 levels would give you variances for the 3 levels so you ...

So 0.06 would be 1 significant figure (number of digits required after leading 0s) so plug that in and see what it says.
Best wishes,
Bill.

P.S. As you say the Brooks Draper diagnostic is how long is required to be confident to quote your estimate as in this case 0.064 rather than say 0.065 or 0.063 which given your effect is non-significant anyway i.e. the SD here is 0.321 and 95% CI is -0.532 to 0.713 might not be really that ...

Morning Manuel,
The purpose of thinning is largely just to make things feasible due to memory constraints etc. so ideally we wouldn't thin at all but clearly the computer then has to store a lot of numbers. As you rightly say we use running totals for ALL iterations to construct the point estimate ...

Hi John,
It is quite common for people to fit random effects to a set of units even if the sampled units are in fact the population. Arguments are made that for example the data is a snapshot in time and thus there would be random uncertainty. A good example is voting data where the dataset is ...

Hi Ferhat,
Happy to take a quick look if you send me the worksheet (william.browne@bristol.ac.uk). We are running a workshop this week so may not be able to get back immediately.
Bill.

Hi Ferhat,
Looking at your variance matrix ALL elements were 0 this means you need to make the matrix positive definite. I think in other places I have suggested making sure the off-diagonal values are 0 which will ensure all correlations are 0 HOWEVER you do need to have all the elements on the ...

Hi FerhatTura,
Chris passed on your query to me but I am not sure how much extra help I can be. Essentially to run the model in MCMC you first need to ensure that the starting values are plausible i.e. that variances are positive and that any covariance matrix is positive definite (essentially that ...