[R-sig-ME] lme vs. lmer

[Ben Bolker]

Douglas Bates wrote:
> On Tue, Sep 29, 2009 at 1:02 PM, Ben Bolker <bolker at ufl.edu> wrote:
> 
>> Christopher David Desjardins wrote:
>>> I've started working through Pinheiro & Bates, 2000 and noticed the use
>>> of lme from the nlme package. I am curious if lmer from lme4 has
>>> superseded lme or if lme still holds its own? The reason I ask is that I
>>> have taken a few classes where we've solely used lmer and just read
>>> about lme today. If both functions are on equal footing, can the
>>> p-values from lme be trusted?
>>> Thanks!
>>> Chris
> 
>>  You should read the extended discussion of p-values, degrees of
>> freedom, etc. that is on the R wiki (I think) and referenced from the R
>> FAQ.  At least in my opinion, (n)lme is still fine (and indeed necessary
>> at this stage for fitting heteroscedastic and correlated models).  The
>> df/p-value estimates, however, are "use at your own risk" -- you'll have
>> to read the literature and decide for yourself.
> 
>>  I still think there's room for someone to implement (at least)
>> Satterthwaite and (possibly) Kenward-Roger corrections, at least for the
>> sake of comparison, but I'm not volunteering.
> 
> You may need to define them first.  Many of the formulas in the mixed
> models literature assume a hierarchical structure in the random
> effects - certainly we used such a formula for calculating the
> denominator degrees of freedom in the nlme package. But lme4 allows
> for fully or partially crossed random effects so you can't think in
> terms of "levels" of random effects.
> 
> Referring to the "Satterthwaite and Kenward-Roger corrections" gives
> the impression that these are well-known formulas and implementing
> them would be a simple matter of writing a few lines of code.  I don't
> think it is.  I would be very pleased to incorporate such code if it
> could be written but, as I said, I don't even know if such things are
> defined in the general case, let alone easy to calculate.
> 
> I am not trying to be argumentative (although of late I seem to have
> succeeded in being that).  I'm just saying that I don't think this is
> trivial. (It I wanted to be argumentative I would say that it is
> difficult and, for the most part, irrelevant. :-)

  Fair enough. Actually, I'm not sure I meant implementing them in lmer
-- even implementing them in nlme would be useful (and perhaps more
straightforward, if not trivial). I also wouldn't impose the requirement
that they have to be feasible for huge data sets -- I'm just curious if
they can be implemented within lme in a relatively straightforward/
boneheaded way.
   But again, this is very far down my to-do list (and at the edge
of my abilities) and completely off yours, so unless someone else bites
it won't happen.

  cheers
    Ben Bolker