[R-sig-ME] nAGQ = 0
Rolf Turner
r.turner at auckland.ac.nz
Thu Sep 7 06:12:56 CEST 2017
On 07/09/17 10:57, Poe, John wrote:
> This is where my being a political scientist on a listserv full of
> definitely not political scientists is going to make me look dumb. I've
> never actually seen a model specification like that before for a
> multilevel model. Is the outcome supposed to be the proportion dead out
> of the total population for each row? I'm missing something about this
> that is probably very obvious.
>
> After fiddling with it I was able to get it to converge for one chain
> but I wouldn't trust it at all right now.
Well, I hadn't seen a model specification quite like that either. It's
brm() syntax, which is a bit different from glm() or glmer() syntax.
The model being fitted is a binomial model, with success probability p
modelled by
g(p) = beta_0 + beta_1 * x + Z_0 + Z_1 * x
where the Z_k are the random effects, and where g() is the link
function, e.g. cloglog(). (I *think* I've got that right.)
Of course beta_0 and beta_1 depend on treatment group and Z_0 and Z_1
depend on "Rep", which is nested within treatment group.
Note that we are talking *generalized* linear mixed models here; the
responses are binomial success counts. "Success" = Dead, since one is
trying to kill the bugs.
For what it's worth the glmer() syntax is
glmer(cbind(Dead,Alive) ~ (0 + Trt)/x + (x | Rep),
family=binomial(link="cloglog"),data=X)
I got the brm() syntax from the vignette; as I said, I'd never seen it
before.
cheers,
Rolf
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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