What Maarten says in his last sentence presumably applies to a
particular kind of model.
It is interesting (to me anyway) that the conditioned reflex to "logit"
among many analysts
is that the root idea is using what we now call the logit function as a
link function for binary
responses. That approach goes back at least as far as 1941.
Extensions e.g. to responses with multiple outcomes are then regarded as
extra tricks building on that.
However, the logit idea has a much longer history for modelling growth
or decay in demography,
ecology, physiology, chemistry etc. for problems with essentially
continuous responses.
The point is elaborated in a graphical context in a note forthcoming in
Stata Journal 8(1).
Nick
[email protected]
Maarten buis
--- Garry Anderson <[email protected]> wrote:
> I was wondering if there is a way that xtlogit can be used with
> fractional response panel data?
> (Other options include glm and the cluster robust variance, or
> xtgee.)
-xtgee- relates to -glm- as -xtlogit- relates to -logit-. So
-xtgee- seems to me the natural way to extend this to approach
to panel data, especially since the fractional logit was
originaly proposed as within the framework of quasi-likelihood.
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