I'm  to ask whether anyone has any experience with cross-classified multi-level models, with repeated measures and interactions in MLwiN?

I have a dataset of with 5 classifications: 3 observations which are at level 1; dogs nested within observations; then dam, sire and supervisor are cross-classified, in addition to a gender/age interaction effect. I can't find any literature to guide me on whether I've set the model up correctly so I'm just wondering if anyone would be able to confirm whether I have it right or not?

The model can be written as:

Responsei ~ N(XB, Ω)
Responsei  = β 0iconsi + β1Age_Group1.Female_1i + β2Age_Group2.Female_1i  + β3Age_Group3.Female_1i
β 0i = β 0 + u(5)0,Sup_ID(i) + u(4)0,Sire_ID(i) + u(3)0,Dam_ID(i) + u(2)0,Dog_ID(i) + e0i
[u(5)0,Sup_ID(i)] ~ N(0, Ω(5)u) : Ω(5)u = [Ω(5)u0,0]
[u(4)0,Sire_ID(i)] ~ N(0, Ω(4)u) : Ω(4)u = [Ω(4)u0,0]
[u(3)0,Dam_ID(i)] ~ N(0, Ω(3)u) : Ω(3)u = [Ω(3)u0,0]
[u(2)0,Dog_ID(i)] ~ N(0, Ω(2)u) : Ω(2)u = [Ω(2)u0,0]
[e 0i] ~ N(0, Ωe) : Ωe = [Ωe0,0]         (Level one is Age_Group)

Any guidance you could give me would be much appreciated.