-----Original Message-----
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
Hi Melanie,
As far as I know, lmer never fixes the residual variance to 1 or any
other
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
residual
variance estimate. If you give us a sample of the code you used, we could
help figure out what happened.
Jake
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
family=binomial.
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,
Melanie