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Thanks!
Katrijn

Dear Chris,

Thank your for your quick reply.

However, I actually do use MCMC (with the cross-classification option turned on).
When I add my country-cohort characteristics, the variable has a lm-subscript (which corresponds to the cohort level).
Do you know whether something else could cause this ...

Dear all,

I am trying to run a model that has a nesting structure as shown in the attached figure.
However, when I want to incorporate a country-cohort characteristic, MLwiN does not recognize it as defined at this level (neither in IGLS, nor in MCMC). MLwiN considers it as a cohort characteristic ...

Dear all,

I want to conduct a two-level nested model using longitudinal data (level1 = observation, level2=ID).
My dependent variable is a binary outcome.

When I try to fit my nullmodel using 2nd order PQL (based on the starting values of 1st order MQL), my model does not converge.
I am not sure ...

Dear Chris,

Thank you very much for your help!
It works!!!

Katrijn

Dear Chris,

The zoom-function worked well.
As you can see, the covariance matrix is not similar to the covariances of the IGLS model
(especially the numbers I changed in column 1096).

Thanks,
Katrijn

Dear Chris,

I cannot scroll down to the bottom to see the priors for the covariance matrix (as I have 65 coefficients).
Is there another way to see them?

Many thanks,
Katrijn

Dear Chris,

Thank you for your quick reply!

I'm using version 2.35, so that cannot be the problem...

I do not exactly understand what you mean, but I added a print screen of my priors (I couldn't see all the priors, but I guess they are all equal to 1).

And no, my dataset only contains 20 ...

Hi

I want to carry out a multinomial multilevel analysis in MlWin, using the Markov Chain Monte Carlo estimation procedure, but I'm having some difficulties.

When I switch from 1st order MQL to 2nd order PQL, I lose all my cases (while my data contains no missing values).
So, I tried to go ...

Dear Chris,

I’m using version 2.31 of MlWin and the data contained no missing values.
The MCMC convergence criteria were met (ESS > 400 and the trajectories look fine).
I added a screenshot and further information as attachment.

Many thanks,
Katrijn