Best way to model repeated measure differences across groups Let's say I have three groups, each consisting of two individuals. Each group answers questions together, and each member independently reports their confidence in their groups' answers.  I want to see if one kind of group has members that are more confident in their collective answer than members of other groups. 
On the one hand, this is a repeated measures problem since the same question is asked multiple times ("what is your confidence?" on a 0-100 scale).  But the measures actually relate to different questions.  There's a temporal component to the problem, since confidence likely evolves over time.  It's also multi-level (individual + group characteristics).  
The most trivial way of dealing with this is by averaging each individual's confidence across all the questions at the group-level and doing a simple comparison of means.  I'm afraid this loses a lot of interesting information, however.  What is the best way to model this?
 A: I imagine a three level longitudinal model would be the starting place:
$$\text{confidence}_{tik}=\pi_{0ik}+\pi_{1ik}(\text{time})+e_{tik}$$
where
$$\pi_{0ik}=\beta_{00k}+\beta_{01k}(\text{sex})+r_{0ik}$$
and
$$\pi_{1ik}=\beta_{10k}+\beta_{11k}(\text{sex})+r_{1ik}$$
with
$$\beta_{00k}=\gamma_{000}+\gamma_{001}(\text{group})+U_{00k}$$
and
$$\beta_{01k}=\gamma_{010}+\gamma_{011}(\text{group})+U_{01k}$$
and
$$\beta_{10k}=\gamma_{100}+\gamma_{101}(\text{group})+U_{10k}$$
and
$$\beta_{11k}=\gamma_{110}+\gamma_{111}(\text{group})+U_{11k}$$
such that
$$\text{confidence}_{tik}=\gamma_{000}+\gamma_{001}(\text{group})+\gamma_{010}(\text{sex})+\gamma_{011}(\text{group})(\text{sex})+\gamma_{100}(\text{time})+\gamma_{101}(\text{group})(\text{time})+\gamma_{110}(\text{sex})(\text{time})+\gamma_{111}(\text{group})(\text{sex})(\text{time})+U_{00k}+U_{01k}(\text{sex})+U_{10k}(t)+U_{11k}(\text{sex})(\text{time})+r_{0ik}+r_{1ik}(t)+e_{tik}$$
However, you should look at the proportional variance explained by the levels and by each variable. Nonetheless, I presume the $(\text{group})(\text{sex})(\text{time})$ three-way interaction will yield very interesting results.
Edit (thanks to a_statistician for catching some issues): The $U$ parameters are level-2 random  effects and level-2 by level-1 random interaction effects.
