[R] Think I'm sure, but confirm: lme4 vs. nlme
Mitchell Maltenfort
mmalten at gmail.com
Wed Oct 22 17:25:51 CEST 2008
Bert, you've been very helpful. It sounds like for my meagre needs,
nlme is what I should stick with. However, I'll wait for Bates to
weigh in on the pros and cons of each. Thanks!
On Wed, Oct 22, 2008 at 11:23 AM, Bert Gunter <gunter.berton at gene.com> wrote:
> Doug Bates is the authority of course, but perhaps a couple of quick inline
> comments may suffice:
>
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
> Behalf Of Mitchell Maltenfort
> Sent: Wednesday, October 22, 2008 7:41 AM
> To: r-help at r-project.org
> Subject: [R] Think I'm sure, but confirm: lme4 vs. nlme
>
> The impression I get from the list and the references I've perused is
> that nlme is being phased out in favor of lme4, but lme4 still doesn't
> have a complete feature set yet.
>
> -- Not exactly. nlme isn't really being phased out (yet anyway) -- it's just
> not being improved anymore. However, it is a pretty nice implementation of
> mixed effects models for continuous data with Gaussian errors with nested
> random effects. And not too large data sets. I would opine that it handles
> the bulk of mixed effects models that one encounters in the physical and
> biological sciences very well.
>
> What I'm still fuzzy on, being a relative R newbie, is:
>
> (a) what features in nlme are currently missing in lme4
> (b) what's the projected time frame on getting them implemented.
>
> -- I think the time frame is "continuing, as Doug is able to work on it." As
> a user, I would say that this is not a discrete event, but an evolving work.
> I use lme4 routinely now.
> As for features, that is difficult to answer. Last I checked, nlme has a
> good predict method but lme4 didn't. lme4 does mcmc for the posterior
> distribution of parameters in Gaussian models, nlme doesn't; but nlme does
> an approximate version of confidence intervals for parameters. Also lme4
> handles glm's, crossed random factors, very large data sets; nlme does none
> of this. Etc. Doug may, of course, have corrections or additions here.
>
> If anyone can answer my naive and impertinent question in a friendly,
> helpful and informative manner[1], I would be delighted. Thanks!
>
> -- I didn't consider your questions naive or impertiment. I leave it to you
> to judge whether I have been friendly or helpful.
>
> Cheers,
> Bert Gunter
>
> [1] Or, translated from craven, "please don't ignite a flame war on my
> no-account account"
>
> Regards,
>
> Mitch
> --
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> deferred until arrears in scheduled gratification have been satisfied.
>
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