Recently a question came up that I felt had several redundant tags for variants of multilevel or mixed-effects models. As far as I can tell, there are six tags I can find that are related to this topic some of which have tag wikis and some do not (for whatever that's worth):
- multilevel (no tag wiki)
- multilevel-analysis (has a tag wiki and has hierarchical-analysis as a synonym)
- mixed-model (informative tag wiki)
- mixed-effect (only four questions tagged, and oldest less than a month ago; no tag wiki)
- random-effects-model (no tag wiki)
- glmm (only four tagged questions, but has an informative wiki)
There are also (at least) two related software tags:
This point has been discussed in a previous meta post by Andy W, but it doesn't seem to have resolved everything; or, perhaps, new developments have arisen in the meantime. I realize there are methodological and semantic differences between some of these terms (as chl and Andy W discussed in the comments of that post), but it still seems like an awful lot of tags...!
Suggestions
- Questions tagged multileveland multilevel-analysis should be merged.
- Questions tagged mixed-model and mixed-effect should be together as well.
- Questions tagged glmm could be merged into the appropriate one of those categories and then also given a generalized-linear-model tag? There are probably questions that are not marked as glmm that should be though...
- The random-effects-model tag deserves a tag wiki. Unless someone else would contribute something more detailed, I would propose something like
Parameters associated with the particular levels of a covariate are sometimes called the “effects” of the levels. If the levels that are observed represent a random sample from the set of all possible levels we call these effects "random."
which is a paraphrase from Douglas Bates' book. (I think unpublished or in press at this point.)
multilevel-analysis
tag: stats.stackexchange.com/questions/22234/…. There should behierarchical-Bayesian
for questions like this, instead. $\endgroup$