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Hi all,

I have a question for you which I can't get my head around for quite some time now & it all has to do with predicted probabilities. I have a data set with a dichotomous dependent variable (thus a binomial model), about 16 independent variables (including some two and three way interactions ...

Hi Chris,

With regard to your first point: I will send you a private message here with my emailaddress, so I can send you some data and scripts.

The second point is somewhat more problematic for me. I'm not sure if I'm getting conflicting results within those variables - the thing is that I'm not ...

...and another even more serious issue, I think.

What I did is akin this (tried d:e and d*e, doesn't matter):

fullmodel <- runMLwiN(Formula = logit(dv, cons) ~ 1 + a + b + c + d + e + f + d:e + d:e:f + (1+a+b+c|group)
, D="Binomial"
, indata = f
, estoptions = estoptions
, MLwiNPath=mlwin ...

Hi, I think I might have found a possible bug. I kept on getting this really annoying error:

Error in `[.data.frame`(indata, , outvars) : undefined columns selected

This is my R2MLwiN call (shortened the formula)
estoptions <- list(xc = TRUE, sort.force = FALSE, EstM=1, x64=TRUE, optimat = TRUE ...