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Re: st: FW: stcrreg: when the proportional hazards assumption fails


From   Steve Samuels <sjsamuels@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: FW: stcrreg: when the proportional hazards assumption fails
Date   Thu, 21 Oct 2010 16:13:45 -0400

-
Zoe-

Ah, I see what you mean. The tvc() coefficients provide evidence of
non-proportionality, but might not provide the correct model. With
regular Cox, we'd stratify by categories of the offending variable, as
you say, but that's not available here. -stcompadj- (from SSC) also
does not provide a stratified analysis.

One possibility: run the model in the two (three?) subgroups of your
ordinal variable that violate proportionality. Compare the separate
cumulative incidence curves to that predicted by -stcrreg- or
-stcompadj-. Perhaps they are close, and you have a good model after
all.

Otherwise, store the estimates of coefficients of the variables common
to all the models and compute weighted averages, weighting by the
inverses of the estimated variances.  I know this is easier said than
done!

Steve

Steven J. Samuels
sjsamuels@gmail.com
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax:    206-202-4783



On Thu, Oct 21, 2010 at 10:06 AM, Steve Samuels <sjsamuels@gmail.com> wrote:
> Zoe:
>
> I don't see that you have a problem. You seem to have a fairly
> complete model if you include the ordinal variable with the tvc() and
> texp() commands, perhaps omitting the non-significant indicator. As
> the Stata 11 Manual states on p 214, it is the coefficients which are
> time varying.
>
> One issue: a three-level variable would have only two indicators, not
> three. Showing your code and results, as the FAQ request, would really
> help avoid this kind of misunderstanding.
>
> Steve
>
> Steven J. Samuels
> sjsamuels@gmail.com
> 18 Cantine's Island
> Saugerties NY 12477
> USA
> Voice: 845-246-0774
> Fax:    206-202-4783
>
> On Thu, Oct 21, 2010 at 4:45 AM, Zoe Hyde <zhyde@meddent.uwa.edu.au> wrote:
>> Hello All,
>>
>> I am wondering what options are available when the proportional hazards assumption doesn't hold in a competing-risks regression.  The assumption holds for my main independent variable of interest, but not for another (ordinal) variable that I'd like to adjust for; fitting it as a time-varying covariate gives a significant result for 2 of its 3 levels.
>>
>> I could get around this by stratifying by this variable in a standard Cox model, but this doesn't seem to be supported (yet) by stcrreg.
>>
>> Are there any alternatives?
>>
>>
>> Regards,
>>
>> Zoe.
>>
>>
>> Western Australian Centre for Health and Ageing (M570)
>> University of Western Australia
>> 35 Stirling Highway, Crawley 6009
>> Western Australia
>>
>> Courier address:
>> Level 6, Ainslie House, Royal Perth Hospital
>> 48 Murray Street, Perth 6000
>>
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>>
>

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