A model with 4 levels of nested random effects 


Model descriptionAn example of a linear regression model with nested random effects (2 levels) is:
y_{ijs}
=
u_{i} + u_{ij} + e_{ijs},
where u_{i} and u_{ij} are the random effects.
In the current example the models is a logistic regression with 4 levels of nesting, i.e. the random effects part looks like:
u_{i} + u_{ij} + u_{ijk} + u_{ijkl}
To effiently implement this model in ADMBRE one must make use of the SEPARABLE_FUNCTION keyword.
In this particular example i=1,...,100, j=1,2, k=1,2 and l=1,2.
So by calling the SEPARABLE_FUNCTION for each value of i, one in effect breaks up the computation
into 100 smaller computations, which helps ADMBRE avoid dealing with large matrices (800x800 in this case).
ResultsIt takes about 12 minutes to fit the model. 