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    <title>topic Proc phreg counting syle process and PH verification in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-phreg-counting-syle-process-and-PH-verification/m-p/928505#M46279</link>
    <description>&lt;DIV&gt;Hi,&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;I want to asses how some specific regulatory intervention (e.g. tax relief) affects time to firms' defaults using survival analysis. Since my covariate of interest is time-dependent (different firms receive tax reliefs in different moments of time, sometimes more than once), I want to use counting process syntax in the following way (I control also for the industry, in which firm operates, by including NACE code):&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;PROC PHREG DATA = my_data
CLASS industry_code
MODEL (tstart, tstop)*endpt(0) = treatment_variable industry_code/ TIES = EFRON RL;
RUN;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;I've read the "Survival Analysis using SAS. A Practical Guide" book by Paul D. Allison. According to the book when using time-dependent covariates the model is no longer a proportional hazard anymore, but it "creates no real problem for the partial likelihood estimation method".&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;My questions are as follows:&lt;/DIV&gt;
&lt;DIV&gt;1. Do I understand correctly that I don't have to verify the PH assumption prior to estimating the model?&lt;/DIV&gt;
&lt;DIV&gt;2. If the answer to the previous question is "yes", are there any other assumptions that I have to verify to make sure that I can estimate the model as shown above?&lt;/DIV&gt;
&lt;DIV&gt;3. Are the ways to asses goodness of fit the same for models with time-dependent covariates and "standard" PH models? Can use the statistics produced by the phreg or I need to adjust them somehow to account for using counting process syntax?&lt;/DIV&gt;</description>
    <pubDate>Wed, 15 May 2024 16:44:01 GMT</pubDate>
    <dc:creator>chris2377</dc:creator>
    <dc:date>2024-05-15T16:44:01Z</dc:date>
    <item>
      <title>Proc phreg counting syle process and PH verification</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-phreg-counting-syle-process-and-PH-verification/m-p/928505#M46279</link>
      <description>&lt;DIV&gt;Hi,&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;I want to asses how some specific regulatory intervention (e.g. tax relief) affects time to firms' defaults using survival analysis. Since my covariate of interest is time-dependent (different firms receive tax reliefs in different moments of time, sometimes more than once), I want to use counting process syntax in the following way (I control also for the industry, in which firm operates, by including NACE code):&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;PROC PHREG DATA = my_data
CLASS industry_code
MODEL (tstart, tstop)*endpt(0) = treatment_variable industry_code/ TIES = EFRON RL;
RUN;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;I've read the "Survival Analysis using SAS. A Practical Guide" book by Paul D. Allison. According to the book when using time-dependent covariates the model is no longer a proportional hazard anymore, but it "creates no real problem for the partial likelihood estimation method".&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;My questions are as follows:&lt;/DIV&gt;
&lt;DIV&gt;1. Do I understand correctly that I don't have to verify the PH assumption prior to estimating the model?&lt;/DIV&gt;
&lt;DIV&gt;2. If the answer to the previous question is "yes", are there any other assumptions that I have to verify to make sure that I can estimate the model as shown above?&lt;/DIV&gt;
&lt;DIV&gt;3. Are the ways to asses goodness of fit the same for models with time-dependent covariates and "standard" PH models? Can use the statistics produced by the phreg or I need to adjust them somehow to account for using counting process syntax?&lt;/DIV&gt;</description>
      <pubDate>Wed, 15 May 2024 16:44:01 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-phreg-counting-syle-process-and-PH-verification/m-p/928505#M46279</guid>
      <dc:creator>chris2377</dc:creator>
      <dc:date>2024-05-15T16:44:01Z</dc:date>
    </item>
    <item>
      <title>Re: Proc phreg counting syle process and PH verification</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-phreg-counting-syle-process-and-PH-verification/m-p/934906#M46602</link>
      <description>&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/24842"&gt;@chris2377&lt;/a&gt;&amp;nbsp;wrote:
&lt;DIV&gt;My questions are as follows:&lt;/DIV&gt;
&lt;DIV&gt;1. Do I understand correctly that I don't have to verify the PH assumption prior to estimating the model?&lt;/DIV&gt;
&lt;/BLOCKQUOTE&gt;
&lt;P&gt;The answer to the first question is "No, you should verify the PH assumption". I am not sure of the underlying rationale of imposing a time-dependent variable on the Cox model. If you do not reject the PH assumption, then it is statistically plausible to get rid of the time-dependent variable.&lt;/P&gt;
&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/24842"&gt;@chris2377&lt;/a&gt;&amp;nbsp;wrote:
&lt;DIV&gt;3. Are the ways to asses goodness of fit the same for models with time-dependent covariates and "standard" PH models? Can use the statistics produced by the phreg or I need to adjust them somehow to account for using counting process syntax?&lt;/DIV&gt;
&lt;HR /&gt;&lt;/BLOCKQUOTE&gt;
&lt;P&gt;See this dissertation for more details:&amp;nbsp;&lt;A href="https://scholarcommons.sc.edu/cgi/viewcontent.cgi?article=5318&amp;amp;context=etd" target="_blank"&gt;Evaluation of Goodness-of-fit Tests for the Cox Proportional Hazards Model with Time-Varying Covariates (sc.edu)&lt;/A&gt;.&lt;/P&gt;</description>
      <pubDate>Sun, 07 Jul 2024 10:31:32 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-phreg-counting-syle-process-and-PH-verification/m-p/934906#M46602</guid>
      <dc:creator>Season</dc:creator>
      <dc:date>2024-07-07T10:31:32Z</dc:date>
    </item>
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