[R-sig-ME] Does glm (and glmer) no longer vectorize proportions when estimating a binomial GLM(M)?

[Jeremy Koster]

A while ago, I posted this message to the listserv:
https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q3/006717.html

Specifically, I had noted that this code:

smoking.aggregated <- glmer (cbind(smoking observations, total observations) ~ AGE + (1|Individual), family = binomial, data = aggregated)

generates the same estimates as this code, which simply uses an unaggregated vector of data with a binary outcome variable instead of the proportions via cbind: 


smoking.unaggregated <- glmer (smoking ~ AGE + (1|Individual), family = binomial, data = unaggregated)


In response, Doug Bates described the underlying code and functions as a bit of a "hack" -- see: https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q3/006724.html

Well, I no longer get the same estimates when using the two above lines of code, which along with Doug's comment makes me wonder if subsequent versions of the base and lme4 packages now treat these models differently.

Thanks, all.