I had a visceral reaction to the binomial, as Pavlos' response is
in principle continuous (although it's an average of a few integers).
However, it may well be that the discreteness of the binomial is not all
crucial here,
rather the shape of its variance function.
People with a closer knowledge of the literature or a deeper theoretical
understanding
may wish to comment.
The binomial is recommended in
http://www.stata.com/support/faqs/stat/logit.html
Nick
[email protected]
Anders Alexandersson
Pavlos C. Symeou <[email protected]> wrote originally:
> I have panel data for 100 firms for five years and I want to examine
the
> effects of various variables on "reputation". My variable
"reputation"
> takes continuous values in the range of 0-10. Namely, it can take
> values of 1,2,3 but also of 2.5, 9.6, etc. The values that the
variable
> "reputation" takes in my sample range between 2.6 - 8.3. Can you
please
> advise if I can still use panel OLS estimation for panel data or
should
> I use a different model? In essence, my main concern is the
limitations
> of the bounded range of my variable.
There were several responses and clarifications. Nick Cox suggested
> gen repute = reputation / 10
> xtgee repute ..., link(logit) family(<continuous>)
Unfortunately this is not allowed, Nick confirmed to Pavlos:
> You are correct in that -xtgee- (Stata 8) does not support -f(gamma)
> link(logit)- or -f(normal) link(logit)-. I was guessing by analogy
with
> -glm- which does support those combinations. I am away from base at
> present and unable to check Stata 10. (I assume from your reference to
> Stata 8 manuals that you are using Stata 8. If that is true, it is
> prudent to flag the fact in your postings.)
>
> I don't know of any reason why those combinations are not supported
by
> -xtgee- when they are by -glm-. As a programmer, I am sympathetic to
any
> explanation of the form "Just didn't think of that" or "Not got round
to
> that yet".
>
> The other link functions are in principle unsuitable, as they pay no
> heed to the range restriction, but you could try
> -link(identity)- and -f(gamma)- or -f(normal)-.
Are we talking about a fractional response on unbalanced panel data?
In that case, how about using using -glm ..., family(binomial)
link(logit) robust- but separately for each panel? That (or with the
probit link) seems to be what Jeffrey Wooldridge suggests at the end
of this paper:
http://www.msu.edu/~ec/faculty/wooldridge/current%20research/clus1aea.pd
f
I'm sure he would be happy to clarify this at 2008 SNASUG, if needed :-)
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