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    <title>topic Re: How to assess confounding in negative binomial regression in SAS Programming</title>
    <link>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926826#M364753</link>
    <description>&lt;P&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/10892"&gt;@PaigeMiller&lt;/a&gt;, apologies for having wasted your time. Thanks again.&lt;/P&gt;</description>
    <pubDate>Thu, 02 May 2024 17:39:18 GMT</pubDate>
    <dc:creator>KKIND</dc:creator>
    <dc:date>2024-05-02T17:39:18Z</dc:date>
    <item>
      <title>How to assess confounding in negative binomial regression</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926821#M364748</link>
      <description />
      <pubDate>Thu, 02 May 2024 16:40:30 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926821#M364748</guid>
      <dc:creator>KKIND</dc:creator>
      <dc:date>2024-05-02T16:40:30Z</dc:date>
    </item>
    <item>
      <title>Re: How to assess confounding in negative binomial regression</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926823#M364750</link>
      <description>&lt;P&gt;Confounding usually refers to the X variables only. You can assess it using PROC REG (and many other procedures) with a fake continuous Y variable. VIF and similar measures are what you want.&lt;/P&gt;</description>
      <pubDate>Thu, 02 May 2024 17:21:17 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926823#M364750</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2024-05-02T17:21:17Z</dc:date>
    </item>
    <item>
      <title>Re: How to assess confounding in negative binomial regression</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926824#M364751</link>
      <description>&lt;P&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/10892"&gt;@PaigeMiller&lt;/a&gt;, thank you very much! What I am trying is running a code with the DV and the primary IV and then running it again adding the variable I am assessing for confounding and checking for the difference in estimates output table. Is difference more than 10% then the variable is a confounder. Does that make sense or do I just look at the p value by running the code&amp;nbsp; DV= IV and the variable, and if significant, consider it a confounder? Thanks!&lt;/P&gt;</description>
      <pubDate>Thu, 02 May 2024 17:27:47 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926824#M364751</guid>
      <dc:creator>KKIND</dc:creator>
      <dc:date>2024-05-02T17:27:47Z</dc:date>
    </item>
    <item>
      <title>Re: How to assess confounding in negative binomial regression</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926825#M364752</link>
      <description>&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/350945"&gt;@KKIND&lt;/a&gt;&amp;nbsp;wrote:&lt;BR /&gt;
&lt;P&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/10892"&gt;@PaigeMiller&lt;/a&gt;, thank you very much! What I am trying is running a code with the DV and the primary IV and then running it again adding the variable I am assessing for confounding and checking for the difference in estimates output table. Is difference more than 10% then the variable is a confounder. Does that make sense or do I just look at the p value by running the code&amp;nbsp; DV= IV and the variable, and if significant, consider it a confounder? Thanks!&lt;/P&gt;
&lt;HR /&gt;&lt;/BLOCKQUOTE&gt;
&lt;P&gt;This should have been explained in your original message. Instead you make me guess at what you want, and waste my time.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I will stick with my original answer, I feel that is a better way to address confounding than your 10% method.&lt;/P&gt;</description>
      <pubDate>Thu, 02 May 2024 17:37:25 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926825#M364752</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2024-05-02T17:37:25Z</dc:date>
    </item>
    <item>
      <title>Re: How to assess confounding in negative binomial regression</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926826#M364753</link>
      <description>&lt;P&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/10892"&gt;@PaigeMiller&lt;/a&gt;, apologies for having wasted your time. Thanks again.&lt;/P&gt;</description>
      <pubDate>Thu, 02 May 2024 17:39:18 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-assess-confounding-in-negative-binomial-regression/m-p/926826#M364753</guid>
      <dc:creator>KKIND</dc:creator>
      <dc:date>2024-05-02T17:39:18Z</dc:date>
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