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Re: st: Small strata and test of proportional hazard assumption


From   Michael McCulloch <mm@pinestreetfoundation.org>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Small strata and test of proportional hazard assumption
Date   Thu, 16 Dec 2010 08:55:10 -0800

Grethe, for the stratified portion of your analyses, with strata so small, you could also provide descriptive results using Kaplan Meier plots.
Michael

On Dec 16, 2010, at 8:48 AM, Steven Samuels wrote:

> --
> 
> With strata so small, you can't check the PH assumption, not with plots and not with residuals. The checks require a reasonable estimate of the survival curve in each stratum, and you can't get one.  The purpose of stratum checks is to assess whether a categorical variable can be a predictor in a Cox model, but a variable such as yours can't be (unless it is ordinal), because the parameters/failures ratio is too high for valid inference. (The max should probably be < 1:10) If you have many small groups with possibly different survival curves, use a frailty (random-effects) model. In -stcox--, frailty models are implemented with the -shared()- and (optionally) the -vce(cluster)- options.
> 
> Steve
> 
> Steven J. Samuels
> sjsamuels@gmail.com
> 18 Cantine's Island
> Saugerties NY 12477
> USA
> Voice: 845-246-0774
> Fax:    206-202-4783
> 
> On Dec 16, 2010, at 4:24 AM, Grethe Søndergaard wrote:
> 
> Hello,
> 
> I am analysing my data using a stratified cox-regression and am trying
> to find out if the proportional hazards assumptions in my model is
> violated. I wanted to test this using the command estat phtest.
> However, I have become aware that you cannot do this, when the stratas
> are very small (each of the stratas contains 2-6 individuals).
> I haven’t been able to find any information about how to test the PH
> assumption when you have very small strata. Does anyone know of such
> test? (Otherwise I am thinking about first running the full model.
> Afterwards I could stsplit my data in two, and run these models. By
> lrtest I could probably test whether there is better goodness of fit
> in the two time-specific models compared to the full model).
> 
> Grethe
> 
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Best wishes,

Michael McCulloch, LAc MPH PhD
Pine Street Foundation
124 Pine Street
San Anselmo, CA 94960-2674
tel:	415-407-1357
fax: 	206-338-2391


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