See [ST] discrete and the works of Stephen Jenkins.
That said, it's not clear that the discreteness is
that crucial here.
Nick
[email protected]
Shon Hiatt
> BACKGROUND
> I have data on 1000 small firms from a survey that was administered in
> 1990. The survey had 140 questions answered by the entrepreneurs
> themselves.
>
> That same interview was administrered exactly a year later in 1991 to
> only those firms who survived/continued from the original 1000
> (N=600).
>
> The interview was again administered three years later in 1994 to
> firms that continued to exist from the original 1000 (N=350).
>
> I don't have information of when the firms disappeared/died; I only
> know that at some point between the administration of the 1st and 2nd,
> and the 2nd and 3rd surveys that some disappeared. There is a firm
> identification number to track the firms that survived. I also don't
> have data on firms that disappeared--only on those that survived.
>
> I am using the variables to explain survival.
>
> QUESTION:
> What is the best way to go about a survival analysis like this where
> Time=1, 2, 4 and I don't know eactly when the firms disappeared
> between the time intervals?
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