[R-sig-ME] glmer with nAGQ > 1

Viechtbauer Wolfgang (STAT) wolfgang.viechtbauer at maastrichtuniversity.nl
Sun Jul 14 14:04:30 CEST 2013


Thanks for the reply. I wasn't aware of the fact that lme4.0/old-lme4 only allowed one grouping variable with nAGQ > 1, but I just tried that out and that is indeed the case. My more pressing concern with the new lme4 however is the possibility of allowing for nonscalar random effects terms. I frequently fit logistic regression models with multiple random effects (like a random intercept for individuals/clusters and a random effect on a dummy variable to allow for variable treatment effects). It would be great to still benefit from the increased accuracy of nAGQ > 1 then. It would be nice if that could be put on the to-do list, but I know from personal experience how those to-do lists have a tendency just to get longer than shorter over time.

Best,
Wolfgang

> -----Original Message-----
> From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-
> bounces at r-project.org] On Behalf Of Ben Bolker
> Sent: Thursday, July 11, 2013 17:36
> To: r-sig-mixed-models at r-project.org
> Subject: Re: [R-sig-ME] glmer with nAGQ > 1
> 
> Viechtbauer Wolfgang (STAT <wolfgang.viechtbauer at ...> writes:
> 
> > I just tried to fit a mixed-effects logistic regression model with
> > version 0.99999911-5 of lme4 (installed from github). The model
> > includes a random effect for clusters and a random group/treatment
> > effect. I received the following error:
> 
> > Error in updateGlmerDevfun(devfun, glmod$reTrms, nAGQ = nAGQ) : nAGQ
> >   > 1 is only available for models with a single, scalar
> >   random-effects term
> 
> > Indeed, I had set nAGQ > 1 to get more precision with the evaluation
> > of the integrals via Gauss-Hermite quadrature. It's clear what the
> > error message says, but I am wondering if this is going to be a
> > permanent design choice or something temporary.
> 
>    It's probably a "foreseeable future" decision (alas).
> 
>    I don't know the guts of the AGQ calculation tremendously well,
> so I don't know exactly what would be involved in constructing
> a multi-dimensional AGQ.  Taking a brief look back at lme4.0/old-lme4,
> it seems that only a single _grouping variable_ was allowed, but
> it was not limited to scalar random effects terms, so it might
> not be too horrible to re-implement ... but it's not on the
> urgent "to do" list at the moment ...  (Anyone want to volunteer
> to take a look at the code and implement this ???)
> 
>   Ben
> 
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