[R-sig-ME] Force the random effects variances to be the same

[Ben Bolker]

  Doesn't lme4qtl allow nAGQ > 1 ?

https://github.com/variani/lme4qtl/blob/0c173ea8d8386b205f62ad642698519a861650b4/R/relmatGlmer.R#L22-L24

   I can't quite see what your groups look like since HTML structure 
gets thrown away by the mailing list ...  is each of the random effect 
scalar (i.e. variance among females, variance among males?)

   Something *approximately* like

glmod <- glFormula(..., data = ..., family = binomial)
devfun <- do.call(mkGlmerDevfun, glmod)
opt <- optimizeGlmer(devfun)
devfun <- updateGlmerDevfun(devfun, glmod$reTrms)

   (These first four steps are just repeating what's in ?lme4:modular))

At this point it gets slightly trickier.

Write a wrapper function that repeats the first element of the given 
parameter vector, then passes it to devfun (in general the random 
effects parameters are at the beginning of the parameter vector); the 
parameter vector for this will be one shorter than the parameter for the 
full model.

devfun2 <- function(p) {
   devfun(c(p[1], p))
}

nfixed <- ## figure out the number of fixed-effect parameters
opt <- nloptwrap(par = c(opt$par[-1], rep(0, nfixed)), fn = devfun2,
    lower = c(0, rep(-Inf, nfixed))

  This should give you the answer, it might take a little more fussing 
to put it back into a merMod object (something like):

opt$par <- c(opt$par[1], opt$par)  ## augment parameter vector
mkMerMod(environment(devfun), opt, glmod$reTrms, fr = glmod$fr)

   I'm not sure all of that is right, but it might be.

  cheers
    Ben Bolker


On 2022-05-13 3:36 a.m., Thierry Onkelinx via R-sig-mixed-models wrote:
> Why would you want to do that?
> 
> ir. Thierry Onkelinx
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> 
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> Op do 12 mei 2022 om 23:29 schreef pluo244 using aucklanduni.ac.nz <
> pluo244 using aucklanduni.ac.nz>:
> 
>> Hi,
>> I would like to use lme4::glmer to fit a model of the form
>> y ~ x + (0+m|group) + (0+f|group)
>>
>> where a group looks like
>> m f1 00 11/2 1/21/2 1/2
>> 1/2 1/2
>>
>> I was wondering if it is possible to force the variances of the random
>> effects to be the same?
>> Many thanks,Zoe
>>          [[alternative HTML version deleted]]
>>
>> _______________________________________________
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>>
> 
> 	[[alternative HTML version deleted]]
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-- 
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
(Acting) Graduate chair, Mathematics & Statistics