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Re: st: Write a parametric survival model in the hazard notation
From
Steve Samuels <[email protected]>
To
[email protected]
Subject
Re: st: Write a parametric survival model in the hazard notation
Date
Sun, 5 Sep 2010 11:40:44 -0400
--
For drawing a hazard function curve, see -stpm2- (and -stpm-) from
SSC. I think that the Stata Journal references are now available for
free download; just google "flexible parametric models royston". You
can use -adjust- after -stpm2- (maybe after -stpm-). I haven't used
either of these programs, so you are on your own. If the generalized
gamma model was good, then don't expect hazards to be proportional.
Steve
On Sun, Sep 5, 2010 at 11:10 AM, Christ, Florian <[email protected]> wrote:
> Dear Steve,
>
> thanks so much for your quick and helpful response. Very insightful!
>
> I will try to fit -stcox- and test the proportional-hazards assumption to see if this is a feasible way to go.
>
> However, I am a bit unsure on how to best draw interactions, when using stcox (Stata version 10). In my model I want to test the effect of multiple interaction terms (2 continuous variables and even one three-way interaction) on the dependent variable (employee turnover). It seems that the at(varname=# ...)-option allows only specific variable values leading to a significant loss of information for my continuous covariates (if my understanding is correct).
>
> Probably you have a helpful solution for this as well?
>
> Thanks so much again for your amazing help and support (especially given my 'newbie' questions).
>
> Best regards,
>
> Florian
>
>
> Florian Christ
>
> WHU – Otto Beisheim School of Management
> Doctoral Research Fellow
> ________________________________________
> Von: [email protected] [[email protected]] im Auftrag von Steve Samuels [[email protected]]
> Gesendet: Sonntag, 5. September 2010 16:28
> An: [email protected]
> Betreff: Re: st: Write a parametric survival model in the hazard notation
>
> --
>
> Florian Christ:
>
> While it is true that any survival model can be written in hazard
> notation, it is _not_ true that the coefficients will necessarily have
> an interpretation in terms of altering hazard ratios. The generalized
> gamma model is what is known as an accelerated failure time model, and
> the effect of the regression variables is to multiply time, not the
> hazard. No transformation of coefficients will remedy this, and a
> rewrite of the likelihood equation will not help.
>
> You _can_ plot hazard functions from the generalized gamma with
> -stcurve-. Use a bootstrap to get get CIs for the difference or ratio
> over a range of time points. As an aside: the BIC comparisons don't
> actually show that the model fit the data well, and residual checks
> and plots will still be necessary.
>
> Bit this is a long way around. To get easier interpretations in terms
> of hazard ratios, I suggest that you fit -stcox- and add interactions
> of covariates and time. Also consider -stpm2- (from SSC) for flexible
> parametric hazard models.
>
> Steve
>
> Steven J. Samuels
> [email protected]
> 18 Cantine's Island
> Saugerties NY 12477
> USA
> Voice: 845-246-0774
> Fax: 206-202-4783
>
> On Sun, Sep 5, 2010 at 6:46 AM, Christ, Florian <[email protected]> wrote:
>> Dear statalisters,
>>
>> I am new to statalist and would greatly appreciate your help with regard to my 'rookie' event-history problem.
>>
>> I am reporting coefficients from a parametric survival model (Generalized gamma distribution; following the AIC and BIC criterion) for my research project. However, as I am examining employee turnover as dependent variable interpretation of coefficients would be easier, if they would equal the hazard notation rather than the survival notation (e.g., positive coefficients should mean that the predictor increases the hazard). E.g., Cleves et al. mention in their great book on p.20 that "any parametric survival model can be written in the hazard notation".
>>
>> So I was wondering if and how I can practically write my survival model (generalized gamma distribution) in the hazard notation? Do I have to write an own maximum likelihood estimator for this? If so, how? Alternatively I may probably just transform the coefficients so that they reflect the hazard logic (probably with estout; transform). If there are other solutions to this problem I would also greatly appreciate your help.
>>
>> Thanks so much in advance for your help and support.
>>
>> Best regards,
>>
>> Florian
>>
>>
>>
>> Florian Christ
>>
>> WHU – Otto Beisheim School of Management
>> Doctoral Research Fellow
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