I found the comment below interesting in one of yesterday's threads, as I am currently analyzing a data set with a random effect fully nested within a fixed factor.  Could anyone elaborate on what is meant by "penalty on the random effect"? Is this also what is deemed "shrinkage"?  How does it work?  Thanks, Paul


"I understand that when a random effect is fully
nested within a fixed effect, the penalty on the random effect
resolves the singularity and allows estimation of both. (That is, if
appropriate, you could model depfemr as a fixed effect?)"



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