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# Re: st: parametric survival analysis - choosing the probability distribution

 From Magdalena Kapelko <[email protected]> To [email protected] Subject Re: st: parametric survival analysis - choosing the probability distribution Date Tue, 7 Jun 2011 22:56:59 +0200

```Maarten, thank you very much for your answer.

Can you suggest me a way to solve the problem that the proportionality
assumption for cox model does not hold? Is there any other model I can
choose from?

Magda

2011/6/7 Maarten Buis <[email protected]>:
> On Tue, Jun 7, 2011 at 1:34 AM, Magdalena Kapelko wrote:
>> I am trying to run survival analysis is STATA, analyzing the impact of
>> some variables on the probability of firm failure. Because the
>> proportionality assumption for cox model does not hold, I run a
>> parametric regression model instead. I want to choose between Weibull
>> and exponential distributions.
>
> Both the Weibull and the exponential also assume proportional hazards,
> so that does not solve your problem.
>
>> Some literature says: compare AIC of
>> different models and choose a model with the lowest AIC. But the
>> problem is that:
>> - for Weibull I obtain very large negative AIC  (aprox. - 20000)
>> - for exponential I obtain positive AIC (aprox. 1000).
>>
>> when choosing the model, shall I look at absolute values of AIC and in
>> this way choose exponential, or shall I choose in general a model with
>> the smallest AIC that is Weibull.
>
> You take the values as is, so you do not take the absolute values.
>
>> Is it possible that for the model
>> with the same independent variables, the assumption of one
>> distribution can give a negative AIC and the other a positive AIC?
>
> yes, see e.g.: <http://blog.stata.com/2011/02/16/positive-log-likelihood-values-happen/>
>
> Hope this helps,
> Maarten
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
>
> http://www.maartenbuis.nl
> --------------------------
>
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