In short, I think not. If y is distributed Poisson with mean x, where
length of transect enters x linearly (with coef 1), then the
probability of seeing y>0 is gammap(1,x) and the logit link does not
make a lot of sense... look at:
tw function y=gammap(1,x),ra(-5 5)||function y=invlogit(x),ra(-5 5)
See also:
findit gammafit
which models y as a function of x implicitly defined by the density
gammaden(ax,bx,0,y)
integrating to one, I believe--I haven't used it (perhaps Nick or
Stephen will comment).
On Fri, Apr 24, 2009 at 9:20 AM, <[email protected]> wrote:
> Dear Statalisters,
>
> I'm investigating the relationship between the number of bats recorded
> along a series of transects and the landscape characteristics of the
> transects. I intend to model the count data using xtpoisson, then convert
> the dependent variable to presence/absence and model using xtlogit.
>
> However, my transects vary in length, which will affect both the number of
> bats encountered and to a lesser extent bat presence/absence. I intend to
> include transect length as an offset when using xtpoisson, but should I
> also include it as an offset when using xtlogit? Does an offset work in
> comparable way with binary data?
>
> Many thanks,
>
> Katherine Boughey
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