[R-sig-ME] A three-level GLMM with binomial link in R
me @end|ng |rom ph||||p@|d@y@com
Sat Mar 6 01:57:44 CET 2021
Since memory seems to be the issue, I would also second trying
MixedModels.jl, which has a somewhat more compact representation of
things that lme4.
If you have a minimal R script, we can get set up with the equivalent
minimal Julia script pretty quickly.
On 5/3/21 10:01 pm, Ben Bolker wrote:
> What kind of estimation issues? As far as just data set size is
> concerned, I would consider this a "medium-to-large" problem for glmer,
> but not something I would expect to cause problems.
> * MASS::glmmPQL is built on top of lme(), so might work well for you
> * glmmTMB provides a more-or-less drop-in replacement for glmer you
> could try
> * GLMMadaptive::mixed_model is another possibility
> * if you really need speed, Doug Bates's MixedModels.jl in Julia
> usually beats everything else listed here
> But ... we could probably give much better advice if you say something
> about the specific kinds of "estimation issues" you're having.
> Ben Bolker
> On 3/5/21 3:27 PM, Hedyeh Ahmadi wrote:
>> Hi All,
>> I was wondering what would be a powerful package in R to run GLMM with
>> logit link that can handle a data set with N=22945 and 3 nested random
>> intercepts. So far, I have tried glmer() from lme4 and it's giving me
>> a lot of estimation issues. Any other package I should try?
>> I am asking for another package as I am having the same issue with
>> lmer() for similar LMM with continuous outcome, while lme() from nlme
>> package runs the models with no problem.
>> Thank you in advance.
>> Hedyeh Ahmadi, Ph.D.
>> Keck School of Medicine
>> Department of Preventive Medicine
>> University of Southern California
>> Postdoctoral Scholar
>> Institute for Interdisciplinary Salivary Bioscience Research (IISBR)
>> University of California, Irvine
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