[R-sig-ME] residual variance estimates fixed to 1
Viechtbauer Wolfgang (SP)
wolfgang.viechtbauer at maastrichtuniversity.nl
Thu Jan 25 00:02:48 CET 2018
For glmer() with family=binomial, there is no 'residual variance'. If you use sigma() to extract it, it will always return 1.
>From: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces at r-
>project.org] On Behalf Of Jake Westfall
>Sent: Wednesday, 24 January, 2018 23:41
>To: Lindner, Melanie
>Cc: r-sig-mixed-models at r-project.org
>Subject: Re: [R-sig-ME] residual variance estimates fixed to 1
>As far as I know, lmer never fixes the residual variance to 1 or any
>value, and in fact this isn't even possible to do with lmer (at least not
>without resorting to add-on packages). My guess is that in your loop you
>accidentally grabbed the wrong field, not the variable giving the
>variance estimate. If you give us a sample of the code you used, we could
>help figure out what happened.
>On Wed, Jan 24, 2018 at 12:02 PM, Lindner, Melanie <
>melanie.lindner at helsinki.fi> wrote:
>> Hi again,
>> I use lme4 to model methylation count data. I specify my response as
>> cbind(methylation count, unmethylation count) and use the argument
>> In my data set I have count information for 500,000 CpG sites over 64
>> samples (so, each sample contains count information for all 500,000
>> 32 per treatment group. I model each site separately to see if there is
>> significant difference between the treatments and therefore use a loop.
>> Since I cannot look at the summary of each site, I saved different
>> estimates from the loop and recognised that the residual standard
>> is always 1. To evaluate the model fit, I would like to understand why
>> residual variance is fixed to one. It would be great if someone can
>> where to find information on that.
>> Thanks in advance,
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