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    <title>topic Re: PH assumptions in PHREG in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/PH-assumptions-in-PHREG/m-p/29165#M1151</link>
    <description>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.  &lt;BR /&gt;
&lt;BR /&gt;
Also, some violations of PH just make the test more conservative.  If so, and A*B may still be a useful test and estimand.</description>
    <pubDate>Fri, 11 Dec 2009 19:41:37 GMT</pubDate>
    <dc:creator>Doc_Duke</dc:creator>
    <dc:date>2009-12-11T19:41:37Z</dc:date>
    <item>
      <title>PH assumptions in PHREG</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PH-assumptions-in-PHREG/m-p/29164#M1150</link>
      <description>Hi All,&lt;BR /&gt;
&lt;BR /&gt;
I'm using PHREG to model some data. &lt;BR /&gt;
&lt;BR /&gt;
so the usual: model time*censored(0) = A B A*B&lt;BR /&gt;
&lt;BR /&gt;
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)&lt;BR /&gt;
&lt;BR /&gt;
My problem is that A and B are categorical not continuous so transforming them is not an option.&lt;BR /&gt;
&lt;BR /&gt;
Any ideas on how to proceed from here????</description>
      <pubDate>Fri, 11 Dec 2009 15:25:16 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PH-assumptions-in-PHREG/m-p/29164#M1150</guid>
      <dc:creator>reb</dc:creator>
      <dc:date>2009-12-11T15:25:16Z</dc:date>
    </item>
    <item>
      <title>Re: PH assumptions in PHREG</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PH-assumptions-in-PHREG/m-p/29165#M1151</link>
      <description>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.  &lt;BR /&gt;
&lt;BR /&gt;
Also, some violations of PH just make the test more conservative.  If so, and A*B may still be a useful test and estimand.</description>
      <pubDate>Fri, 11 Dec 2009 19:41:37 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PH-assumptions-in-PHREG/m-p/29165#M1151</guid>
      <dc:creator>Doc_Duke</dc:creator>
      <dc:date>2009-12-11T19:41:37Z</dc:date>
    </item>
    <item>
      <title>Re: PH assumptions in PHREG</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PH-assumptions-in-PHREG/m-p/29166#M1152</link>
      <description>Thanks. I'll look into that. &lt;BR /&gt;
&lt;BR /&gt;
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?&lt;BR /&gt;
&lt;BR /&gt;
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</description>
      <pubDate>Sat, 12 Dec 2009 14:48:15 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PH-assumptions-in-PHREG/m-p/29166#M1152</guid>
      <dc:creator>reb</dc:creator>
      <dc:date>2009-12-12T14:48:15Z</dc:date>
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