modelling proportions, with aggregated data, and the new/old lme4
Joerg Luedicke <joerg.luedicke at ...> writes:
I would certainly check out a Poisson model with the number of successes as outcome and successes+failures as an offset.
That seems odd to me; the Poisson+offset model should be appropriate when p<<1 (i.e. for very small p, the Poisson variance mu=n*p is approximately the same as the binomial variance n*p*(1-p); in this case p is not small. Of course, I could be wrong.
On Sun, Mar 18, 2012 at 11:51 AM, Rolf Turner <r.turner at ...> wrote:
On 19/03/12 07:10, Ben Bolker wrote: <SNIP>
head(dat) ? successes failures id sex subdist 1 ? ? ? 560 ? ? ?726 ?1 ? F ? ? ? 4 2 ? ? ? 844 ? ? ?510 ?1 ? M ? ? ? 4
[snip]
In community #1, which is in subdistrict #4, there are 560 women
? you mean 510, right?
<SNIP> Sure looks like 560 to me. ?Time for a trek to the optometrist, Ben?
Looked at the wrong line (failures in men rather than successes in women).