[R-sig-ME] "General" (non-Bernoulli) binomial models in GLMMadaptive.

[Rolf Turner]

On 4/08/19 10:10 PM, D. Rizopoulos wrote:

> The current CRAN version of GLMMadaptive should work for binomial data.
> For example, this run in my machine:
> 
> library("GLMMadaptive")
> library("lme4")
> system.time(fm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
>               data = cbpp, family = binomial, nAGQ = 21))
> 
> system.time(gm1 <- mixed_model(cbind(incidence, size - incidence) ~ period, random = ~ 1 | herd,
>                     data = cbpp, family = binomial(), nAGQ = 21))
> 
> 
> summary(fm1)
> summary(gm1)

Thanks very much for this.  And whew! That's a relief, since neither of 
my proposed work-arounds seems to work worth a damn.

May I just ask a quick (said he, optimistically) follow-up question? 
Can you provide a rationale for the choice of nAGQ = 21?  (If this would 
require a lengthy discourse, don't worry about it.)

cheers,

Rolf

P.S.  I gather, from an off-list OOO response that I received, that
you are on a conference/vacation trip.  My apologies for pestering you 
under these circumstances. I hope that you are having an enjoyable time.

R.

-- 
Honorary Research Fellow
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276