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Re: st: parents breaking up - multiple failure survival data w. the Anderson-Gill model
From
Austin Nichols <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: parents breaking up - multiple failure survival data w. the Anderson-Gill model
Date
Fri, 15 Jul 2011 15:29:56 -0400
Tinne--
This is very interesting data! Switch to discrete time hazard models
and maybe semiparametric methods
On Friday, July 15, 2011, Tinne Steffensen <[email protected]> wrote:
> Dear Statalist.
> I have a dataset containing 135.000 children - and information on their parents in a time period from 1980-2007. I'm only interested in them after the year of the id's birth. So for some id's I have observations for 4 years others over a 20 year time-period.
>
> I am interested in analyzing the hazard ratios of the parents breakup(=move from shared address). However there is a possibility of the parents breaking up several times during the period, so I wanted to use the multiple failure-time survival data. t 0 is the birth of my id, t is years after the birth and livetog is if the parents live together that year or not.
>
> Stset, id year
>
> To give you an example:
> +------------------------------------------------------+
> | id group t0 t breakup livetog Inc |
> |------------------------------------------------------|
> | 1 treatment 0 1 0 1 3 |
> | 1 treatment 1 2 0 1 3 |
> | 1 treatment 2 3 0 1 4 |
> | 1 treatment 3 4 1 0 3 |
> |------------------------------------------------------|
> | 2 treatment 0 1 0 0 0 |
> | 2 treatment 1 2 0 0 2 |
> | 2 treatment 2 3 0 0 2 |
> |------------------------------------------------------|
> | 3 control 0 1 0 0 3 |
> | 3 control 1 2 0 1 4 |
> | 3 control 2 3 1 0 1 |
> | 3 control 3 4 0 1 2 |
> | 3 control 4 5 1 0 2 |
> +------------------------------------------------------+
>
> I have tried following the guideline from http://www.stata.com/support/faqs/stat/stmfail.html - ordered failure events "The Anderson-Gill model". So that there for each id is one observation per event or time interval, I've created the variables var"i" - it looks like the following;
>
> +------------------------------------------------------+
> | id group t0 t break livetog Inc t0i ti breaki|
> |--------------------------------------------------------------------------|
> | 1 treatment 0 1 0 1 3 0 3 1 |
> | 1 treatment 1 2 0 1 3 3 4 0 |
> | 1 treatment 2 3 1 1 4 . . . |
> | 1 treatment 3 4 0 0 3 . . . |
> |-------------------------------------------------------------------------|
> | 2 treatment 0 1 0 0 0 0 3 0 |
> | 2 treatment 1 2 0 0 2 . . . |
> | 2 treatment 2 3 0 0 2 . . . |
> |-------------------------------------------------------------------------|
> | 3 control 0 1 0 0 3 . . . |
> | 3 control 1 2 0 1 4 . . . |
> | 3 control 2 3 1 0 1 0 3 1 |
> | 3 control 3 4 0 1 2 . . . |
> | 3 control 4 5 1 0 2 3 5 1 |
> +-------------------------------------------------------------------------+
>
> Along the line of the Anderson-Gill model I have done;
>
> Stset ti, fail(breaki) exit(ti .) id(id) enter(t0i)
>
> But following error comes up: option exit invalid.
>
> 1. Isn't it right to put exit(time i.) since I want to keep the id's after their first breakup and until the observation runs out.
> 2. It seems wrong to follow the Anderson-Gill model, when creating so many missings - but in the guideline (3.2.1) there are only observations for the times of event, so that is what I tried creating. Is the missing values for the "i" variables not excluding the values for group and income in the other years from the model? I have a lot of other variables than group and income, that I want to add to the model along the way.
> 3. Furthermore I would like to include that breaking up (moving from shared address) is only possible when living together - how do I take this into consideration in my model?
>
> I have tried reading the guideline, extracts from "An introduction to survival analysis using Stata", googling, reading old statalist posts etc., but I can't seem to find a solution. I hope you can help!
>
> Thank you for your time.
> Kind regards, Tinne S.
>
>
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>
*
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