# Is it possible to put weights on clusters in MixedModels.jl?

The package currently supports “case weights” - weights on individual observations. I wonder if there is a way to tweak the code so that I can put weights on clusters?

Specifically, the package currently can take a vector of observation weights w , and calculate the total log-likelihood as \sum log(w_ij * P(y_ij)) , where w_ij and y_ij are the weight and response for observation j from cluster i .

However, instead of weighting the probabilities on the observation level, I want to weight the log-likelihood on the cluster level, i.e., I want to calculate \sum w_i l_i ? Here w_i and l_i are the weight and the log-likelihood for cluster i .

Can anyone give a pointer on where I should get started? Thank you.