Dear all, I am a new member (although long time reader) to the list.

My motivation for finally joining is to clearify a (for me) very confusing issue. I apologize beforehand if I have missed any standard or crucial information.

I am analyzing data from a learning experiment with the following structure:

30 subjects with 70 binary resposes each. These respones are ordered by Phase(Factor w/ 2 levels) within subject, where each Phase level is associated with 35 responses.
The subjects are nested within Group(Factor w/ 2 levels), but have an unique index (1:30).

I am interested in the Phase*Group interaction. My orginal model was just lmer(response ~ Group*Phase+(Phase|Subject),family=binomial(link="logit"),data=data), since this seem to be the logical and standard formulation for models with both within and beteen -subjects predictors.

For various obscure reasons, I fitted lmer(response ~ Group*Phase+(Phase*Group|Subject)), which I expected to fail since no Subject belong to both groups (I double checked ...).
However, lmer gladly accepted this and gave by-subject random effects for both the Group effect and the Phase*Groupp interaction.

As far as I see, this situation is identical to trying to fit random slopes for Gender for each subject....

How is this possible? What am i missing?

kind regards
Björn

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