# A model with 4 levels of nested random effects
ADMB Files
Code: nested4.tpl Data: nested4.dat Initial values: nested4.pin Expected Results: nested4.par
| ### Model description An example of a linear regression model with nested random effects (2 levels) is: yijs = ui + uij + eijs, where ui and uij 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: ui + uij + uijk + uijkl To effiently implement this model in ADMB-RE 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 ADMB-RE avoid dealing with large matrices (800x800 in this case). ### Results It takes about 1-2 minutes to fit the model.