Kenneth F Greene wrote:
> 1. The observations are country-election-years
> 2. The DV is the vote percent gap between the winning party and the first loser
> 3. I use a LDV in some specifications and not in others, but the main model does not contain a LDV
> 4. I have an average of 7.9 time points (elections) per country and 55 total observations.
>
> For reasons that are aren't helpful for present purposes, the data set used to be larger and I used xtgee, i(id) robust with success. Now that the data set is smaller, xtgee does not converge. I can make it converge by changing the tolerance, although I'm not yet sure what that actually does and how best to play with it, if at all.
Thanks for the extra details.
Hmmm, not sure why you would use -xtgee- on this data given the way
your DV is measured, but I'll make two suggestions:
(1) if you want your model to obey a panel structure, then using
-xtpcse- with or without the -corr(ar1)- option seems reasonable here;
or
(2) if you're indifferent, then you could normalize your DV and fit a
fractional logit model: -glm y x1 x2 ... xk, fam(bin) link(logit)
robust-.
Both (1) and (2) can accept LDVs, and I've not yet read a rationale as
to why you shouldn't include them in (2).
Hope that helps.
--
Clive Nicholas
[Please DO NOT mail me personally here, but at
<[email protected]>. Please respond to contributions I make in
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"My colleagues in the social sciences talk a great deal about
methodology. I prefer to call it style." -- Freeman J. Dyson.
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