Thank you,Rodrigo. That's helpful.
Caroline
On 4/23/06, Rodrigo A. Alfaro <ralfaro76@hotmail.com> wrote:
> Dear Caroline,
>
> The command -clogit- means Conditional Logit... this is not exactly
> fixed-effects models as we have in the linear regression [Check the math in
> a textbook]. The logit function allows us to "remove" the fixed-effects
> component in the cases that you observe different pattern in your dependent
> variable (let's say y). This means that all cases where y does not change
> over time are useless (as you saw in the error message).
>
> Why? y can be 0 or 1, simplify your life using a linear model with fixed
> effects: y(i,t)=b*x(i,t)+a(i)+e(i,t). In the within variation you will see
> that y(i,t)-y(i,.) is zero for the individuals with not change in y.
> Then -clogit- drops these observations as -xtreg- will drop too.
>
> If your x(i,t) is uncorrelated with a(i) you could use random-effects
> model -help xtlogit-, remember to check the quadrature after the estimation
> to be sure that the numerical approximation is stable, -help quadchk-
>
> Rodrigo.
>
>
>
>
>
>
> ----- Original Message -----
> From: "Caroline Xu" <caroxu@gmail.com>
> To: <statalist@hsphsun2.harvard.edu>
> Sent: Saturday, April 22, 2006 11:29 PM
> Subject: st: clogit
>
>
> Dear Statalist,
>
> I use "clogit" to control some individual fixed effects and got this
> message.
> "note: multiple positive outcomes within groups encountered.
> note: 1378 groups (1399 obs) dropped due to all positive or
> all negative outcomes."
> The number of observations dropped is almost 1/3 of the total number
> of observations. Will this cause any problem on the estimated results?
>
> After control for the individual fixed effects, the PseudoR2 increase
> from 0.12 (logit model) to 0.60. I'm not sure what this implies? It
> means unobserved individual effects are very important for making
> prediction? or Is this increase in PseudoR2 caused by the drop of # of
> observations?
>
> If I want to control for both year and individual fixed effects in the
> logit model, what should I do?
>
> Thanks a lot,
>
> Caro
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