new package suggestion: mmrm about mixedmodels HOT 9 CLOSED

I also think this could be useful, although it is of course a bit tricky since essentially any package for mixed-effects models can handle repeated measures. So we should focus on packages that specifically target this type of application (like mmrm).

from mixedmodels.

Would it fit under "convenience wrappers"? It doesn't appear to be introducing new functionality, but it is providing a wrapper for particular circumstances.

from mixedmodels.

As far as I can tell, it's not just a wrapper around gls() (the way I phrased it was a bit misleading), but I didn't dig into the code.

from mixedmodels.

I saw it as a wrapper for TMB, which is great, because that package is hard to use. There are already many packages that handle repeated measures in this TV and other example where specialized covariance are used (e.g. "spatial"). It might make more sense to redefine that as "specialized covariance structure" or something like that for spatial and repeated measures examples.

from mixedmodels.

A little bit more history/context here: I worked a little bit with the lead author of this package (Daniel Sabanes Bove) to try to implement Satterthwaite df computations for glmmTMB. We got somewhere, but we had trouble with the combination of Satterthwaite dfs and "zero-residual-variance" settings (i.e., implementing "R-side" covariance structures, in SAS terminology), so he decided to write this package instead that implements a certain class of models in TMB.

from mixedmodels.

I"m in favor of a repeated measures section. We will need to sweep through the entire TV to find all those packages.

from mixedmodels.

okay, I'll create a branch and see how it goes.

from mixedmodels.

going to work on this now.

from mixedmodels.

This was added under a new subsection for "specialized models".

from mixedmodels.