lme4 (402) is an R package that has lmer (498), glmer (168), and nlmer (10) functions.
nlme (119) is an R package that has lme (196) as a function.
Both packages fit [generalized] linear (and nonlinear) mixed models. Many questions deal with both packages.
Is it useful to have all these separate tags?
The problem is that it seems that, e.g., [lme4]
and [lmer]
are often used almost interchangeably. And in general, such a deep tag nesting is a bit annoying; e.g., every Q with [lmer]
could/should also be tagged with [lme4]+[mixed-models]+[r]
, i.e., this automatically eats up 4 out of 5 possible tags.
So one could consider mapping all functions to the respective packages. This would end up with [lme4]
with 906 Qs and [nlme]
with 294 Qs. Or perhaps even map everything together to [nlme-lme4]
(or something like that) with 1138 Qs.
Or is it a bad idea?
nmle
are not actually specific tonlme
at all. $\endgroup$[lme4-nlme]
? Or[lme4-etc]
? My personal favourite is[lme4-and-all-that]
. $\endgroup$[lme4-nlme]
since the rest of "all that" is much less used than the two main packages. lme4 is nowadays more popular, but nlme is still popular. Moreover, "all that" can be ambiguous and I imagine that many people could consider very different things as "all that" (e.g. anything related to mixed-effect models). $\endgroup$