<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: VIF and categorical variables in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/VIF-and-categorical-variables/m-p/673407#M32225</link>
    <description>&lt;P&gt;I think it is impossible.&lt;/P&gt;
&lt;P&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/13684"&gt;@Rick_SAS&lt;/a&gt;&amp;nbsp; wrote a blog about VIF before, maybe Rick could say something about it.&lt;/P&gt;</description>
    <pubDate>Thu, 30 Jul 2020 12:52:21 GMT</pubDate>
    <dc:creator>Ksharp</dc:creator>
    <dc:date>2020-07-30T12:52:21Z</dc:date>
    <item>
      <title>VIF and categorical variables</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/VIF-and-categorical-variables/m-p/673401#M32224</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;
&lt;P&gt;I 've heard about the variance inflated factor on the SAS Statistics 1 elearning. I see that on the course, VIF is always performed on continuous variables inputs with the REG procedure (which doesn't accept the "Class" option). I was wondering if there were any ways to perform a VIF analysis with categorical variables at all ?&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Thank you for your help&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Thu, 30 Jul 2020 12:47:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/VIF-and-categorical-variables/m-p/673401#M32224</guid>
      <dc:creator>Mathis1</dc:creator>
      <dc:date>2020-07-30T12:47:27Z</dc:date>
    </item>
    <item>
      <title>Re: VIF and categorical variables</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/VIF-and-categorical-variables/m-p/673407#M32225</link>
      <description>&lt;P&gt;I think it is impossible.&lt;/P&gt;
&lt;P&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/13684"&gt;@Rick_SAS&lt;/a&gt;&amp;nbsp; wrote a blog about VIF before, maybe Rick could say something about it.&lt;/P&gt;</description>
      <pubDate>Thu, 30 Jul 2020 12:52:21 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/VIF-and-categorical-variables/m-p/673407#M32225</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2020-07-30T12:52:21Z</dc:date>
    </item>
    <item>
      <title>Re: VIF and categorical variables</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/VIF-and-categorical-variables/m-p/673411#M32226</link>
      <description>&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;Generate dummy variables and run the VIF on them. For a basic GLM parameterization,&amp;nbsp; you can &lt;A href="https://blogs.sas.com/content/iml/2016/02/22/create-dummy-variables-in-sas.html" target="_self"&gt;use the GLMMOD procedure to generate the design matrix&lt;/A&gt;. Be sure to include only the first k-1 dummy variables for a categorical variable with k levels.&lt;/P&gt;</description>
      <pubDate>Thu, 30 Jul 2020 12:57:39 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/VIF-and-categorical-variables/m-p/673411#M32226</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2020-07-30T12:57:39Z</dc:date>
    </item>
  </channel>
</rss>

