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12-11-2009 10:25 AM

Hi All,

I'm using PHREG to model some data.

so the usual: model time*censored(0) = A B A*B

The PH assumptions are fine for A and B independantly, but are violated for A*B (i have to uset he Hazardratio statement to get HRs for A*B)

My problem is that A and B are categorical not continuous so transforming them is not an option.

Any ideas on how to proceed from here????

I'm using PHREG to model some data.

so the usual: model time*censored(0) = A B A*B

The PH assumptions are fine for A and B independantly, but are violated for A*B (i have to uset he Hazardratio statement to get HRs for A*B)

My problem is that A and B are categorical not continuous so transforming them is not an option.

Any ideas on how to proceed from here????

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12-11-2009 02:41 PM

Depending on the context, you could stratify on A and then have just B A*B in the model. We have had to do that on occasion when the treatment group (A) did not meet PH. You'll still need to look at A*B for PH, but it may finess the problem.

Also, some violations of PH just make the test more conservative. If so, and A*B may still be a useful test and estimand.

Also, some violations of PH just make the test more conservative. If so, and A*B may still be a useful test and estimand.

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12-12-2009 09:48 AM

Thanks. I'll look into that.

A is infection status (control/infected) and B is time in study (early/late) A and B dont make sense if considered alone in this model so it is the interaction that is most important - this ends up comparing control/infected early in study and control/infected late, so stratifying on time in study (B) is feasible. Will that work even though i have a clustering factor of farm (so an ID Farm statement) in the model?

I hadnt considered that some PH assumptions make the test more conservative. How would i know if this is the case with this violation? Message was edited by: reb

A is infection status (control/infected) and B is time in study (early/late) A and B dont make sense if considered alone in this model so it is the interaction that is most important - this ends up comparing control/infected early in study and control/infected late, so stratifying on time in study (B) is feasible. Will that work even though i have a clustering factor of farm (so an ID Farm statement) in the model?

I hadnt considered that some PH assumptions make the test more conservative. How would i know if this is the case with this violation? Message was edited by: reb