'Like' function (Binomial models)

[maelsu91]

Hi,
I'm very new to MLwiN and multilevel modelling, and am trying to replicate an analysis of some data that was completed using MLwiN. They have used a two level binomial model, and compared models with and without interaction terms using the Likelihood Ratio Statistic. These are my problems:
1) When you use the 'like' command in the command interface does it give you -2*log(likelihood) or 2*log (likelihood)? There is some descrepancy between teaching materials and the help pages
2) If it does give you -2*log(likelihood), why does the null model (no interaction terms etc) have a lower value of -2*log(likelihood) than the model with the interaction terms included?

I fitted the models using MQL1 then PQL2 (and dabbled in MCMC but the ESS was tiny and the correlation very high)
Thanks

[ChrisCharlton]

Discrete response models within MLwiN are estimated using quasi-likelihood rather than maximum likelihood, which means that it isn't possible to calculate a likelihood statistic for these models and this is why it isn't displayed in the equation window. In order to compare these models it is recommended that you use a Wald test instead.