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zero random effect sizes with binomial lmer
3 messages · Daniel Ezra Johnson, Gregor Gorjanc
Daniel Ezra Johnson <johnson4 <at> babel.ling.upenn.edu> writes: ...
If one compares the random effect estimates, in fact, one sees that they are in the correct proportion, with the expected signs. They are just approximately eight orders of magnitude too small. Is this a bug?
... BLUPs are essentially shrinkage estimates, where shrinkage is determined with magnitude of variance. Lower variance more shrinkage towards the mean - zero in this case. So this is not a bug. Gregor
Daniel Ezra Johnson <johnson4 <at> babel.ling.upenn.edu> writes: ...
More broadly, is it hopeless to analyze this data in this manner, or else, what should I try doing differently? It would be very useful to be able to have reliable estimates of random effect sizes, even when they are rather small.
... You might try with mcmcsamp to get a better view of posterior distributions of your parameters. It might be the case that MLE for item variance is near 0, while its posterior distribution covers also values that are higher than 0. Gregor