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    <title>topic Survival analysis with time-dependent covariates - model specification in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Survival-analysis-with-time-dependent-covariates-model/m-p/918565#M45588</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. I have around 130 thousand firms, around 6% default cases.&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;Each firm can receive treatment (regulatory intervention) in a different moment of time and more than once, so I use time‐dependent covariates approach as in &lt;A href="https://support.sas.com/resources/papers/proceedings12/168-2012.pdf" target="_self"&gt;this paper&lt;/A&gt;&amp;nbsp;and reshape my original dataset to the "counting process style".&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;In my model I want to control also for the industry in which each firm operates as the treatment is somehow linked to this.&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;So, following the paper linked above, I use the following 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;where:&lt;/DIV&gt;
&lt;DIV&gt;- tstart and tstop are the boundaries of time periods created in accordance with "counting process style"&lt;/DIV&gt;
&lt;DIV&gt;- endpt(0) - shows if each period ends in default or not&lt;/DIV&gt;
&lt;DIV&gt;- industry_code - a 4-digit NACE code of the industry&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;Now I have two questions:&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;1. Is it correct to use &lt;A href="https://ec.europa.eu/eurostat/statistics-explained/index.php?title=NACE_background" target="_self"&gt;NACE industry code&lt;/A&gt;&amp;nbsp;both in the class and model statement? It's just a set of digits with no interpretation - should I transform it and create a set of dummies instead?&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;2. As regards the treatment_variable: one way of specyfing this variable is the value of treatment in a given tstart-tstop period. What about specyfing it as a dummy showing whether the firm was at all subject to treatment or not? This would not be time-variant but time-fixed. Can I include it in the model with counting process setup? This dummy would be created as follows:&lt;/DIV&gt;
&lt;DIV&gt;firm 1: was subject to regulatory intervention twice, in 2010Q4 and 2011Q1, and did not default -&amp;gt; treatment dummy = 1&lt;BR /&gt;firm 2: was not subject to regulatory intervention and did not default -&amp;gt; treatment dummy = 0&lt;BR /&gt;firm 3: was subject to regulatory intervention once in 2010Q3 and went into default in 2011Q4 -&amp;gt; treatment dummy = 1&lt;BR /&gt;firm 4: was not subject to regulatory intervention and went into default in 2012Q1 -&amp;gt; treatment dummy = 0&lt;/DIV&gt;</description>
    <pubDate>Fri, 01 Mar 2024 11:26:01 GMT</pubDate>
    <dc:creator>chris2377</dc:creator>
    <dc:date>2024-03-01T11:26:01Z</dc:date>
    <item>
      <title>Survival analysis with time-dependent covariates - model specification</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Survival-analysis-with-time-dependent-covariates-model/m-p/918565#M45588</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. I have around 130 thousand firms, around 6% default cases.&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;Each firm can receive treatment (regulatory intervention) in a different moment of time and more than once, so I use time‐dependent covariates approach as in &lt;A href="https://support.sas.com/resources/papers/proceedings12/168-2012.pdf" target="_self"&gt;this paper&lt;/A&gt;&amp;nbsp;and reshape my original dataset to the "counting process style".&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;In my model I want to control also for the industry in which each firm operates as the treatment is somehow linked to this.&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;So, following the paper linked above, I use the following 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;where:&lt;/DIV&gt;
&lt;DIV&gt;- tstart and tstop are the boundaries of time periods created in accordance with "counting process style"&lt;/DIV&gt;
&lt;DIV&gt;- endpt(0) - shows if each period ends in default or not&lt;/DIV&gt;
&lt;DIV&gt;- industry_code - a 4-digit NACE code of the industry&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;Now I have two questions:&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;1. Is it correct to use &lt;A href="https://ec.europa.eu/eurostat/statistics-explained/index.php?title=NACE_background" target="_self"&gt;NACE industry code&lt;/A&gt;&amp;nbsp;both in the class and model statement? It's just a set of digits with no interpretation - should I transform it and create a set of dummies instead?&lt;/DIV&gt;
&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;DIV&gt;2. As regards the treatment_variable: one way of specyfing this variable is the value of treatment in a given tstart-tstop period. What about specyfing it as a dummy showing whether the firm was at all subject to treatment or not? This would not be time-variant but time-fixed. Can I include it in the model with counting process setup? This dummy would be created as follows:&lt;/DIV&gt;
&lt;DIV&gt;firm 1: was subject to regulatory intervention twice, in 2010Q4 and 2011Q1, and did not default -&amp;gt; treatment dummy = 1&lt;BR /&gt;firm 2: was not subject to regulatory intervention and did not default -&amp;gt; treatment dummy = 0&lt;BR /&gt;firm 3: was subject to regulatory intervention once in 2010Q3 and went into default in 2011Q4 -&amp;gt; treatment dummy = 1&lt;BR /&gt;firm 4: was not subject to regulatory intervention and went into default in 2012Q1 -&amp;gt; treatment dummy = 0&lt;/DIV&gt;</description>
      <pubDate>Fri, 01 Mar 2024 11:26:01 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Survival-analysis-with-time-dependent-covariates-model/m-p/918565#M45588</guid>
      <dc:creator>chris2377</dc:creator>
      <dc:date>2024-03-01T11:26:01Z</dc:date>
    </item>
    <item>
      <title>Re: Survival analysis with time-dependent covariates - model specification</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Survival-analysis-with-time-dependent-covariates-model/m-p/918850#M45613</link>
      <description>&lt;P&gt;Answering your questions in order:&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;1. Yes, the industry code variable should be included in the class statement. You do not need to create dummy variables yourself.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;2. If you know that your treatment variable actually is time-varying, I recommend modeling it that way.&amp;nbsp;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 04 Mar 2024 16:25:13 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Survival-analysis-with-time-dependent-covariates-model/m-p/918850#M45613</guid>
      <dc:creator>Mike_N</dc:creator>
      <dc:date>2024-03-04T16:25:13Z</dc:date>
    </item>
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