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    <title>topic Re: Proc glimmix dist=multinomial link=logit in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-glimmix-dist-multinomial-link-logit/m-p/712124#M34435</link>
    <description>&lt;P&gt;Thank you for your proposal. We suspected that the near-complete separation was the cause of the problem, but we were surprised by the lack of warning from SAS. We are going to test the surveylogistic proc.&lt;BR /&gt;Thank you again for your support.&lt;/P&gt;</description>
    <pubDate>Mon, 18 Jan 2021 14:38:00 GMT</pubDate>
    <dc:creator>tlse31</dc:creator>
    <dc:date>2021-01-18T14:38:00Z</dc:date>
    <item>
      <title>Proc glimmix dist=multinomial link=logit</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-glimmix-dist-multinomial-link-logit/m-p/711014#M34396</link>
      <description>&lt;P&gt;I have two programs which give me contradictory results for a calculation of the number of subjects per simulation.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Here enclosed, the SAS program perform with the 2 GLIMMIX models:&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;Model1 with 4 groups (A B C P)&lt;/LI&gt;&lt;LI&gt;Model2 with 2 groups (A P) only&lt;/LI&gt;&lt;/UL&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The Results of the "A -P" comparisons are the opposite M1: "A-P" p&amp;lt;0.001 / M2: "A-P" p=0.971.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks in advance for your help.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 13 Jan 2021 08:37:06 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-glimmix-dist-multinomial-link-logit/m-p/711014#M34396</guid>
      <dc:creator>tlse31</dc:creator>
      <dc:date>2021-01-13T08:37:06Z</dc:date>
    </item>
    <item>
      <title>Re: Proc glimmix dist=multinomial link=logit</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-glimmix-dist-multinomial-link-logit/m-p/711078#M34402</link>
      <description>&lt;P&gt;If you do a cross-tabulation of the data in ZZ using PROC FREQ, you will see that when you restrict the dataset to just A and P categories you have quasi-complete separation.- the max for A is yvalue 3 with one obs, the min for P is yvalue3 with one obs.&amp;nbsp; When you fit all the levels, this isn't a problem, but when you restrict like this, the estimation technique results in a poor fit.&amp;nbsp; What I would suggest is using PROC SURVEYLOGISTIC (since you have no random effects).&amp;nbsp; Somehow, it gives reasonable results for these data.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;SteveDenham&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 13 Jan 2021 13:32:03 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-glimmix-dist-multinomial-link-logit/m-p/711078#M34402</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2021-01-13T13:32:03Z</dc:date>
    </item>
    <item>
      <title>Re: Proc glimmix dist=multinomial link=logit</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-glimmix-dist-multinomial-link-logit/m-p/712124#M34435</link>
      <description>&lt;P&gt;Thank you for your proposal. We suspected that the near-complete separation was the cause of the problem, but we were surprised by the lack of warning from SAS. We are going to test the surveylogistic proc.&lt;BR /&gt;Thank you again for your support.&lt;/P&gt;</description>
      <pubDate>Mon, 18 Jan 2021 14:38:00 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-glimmix-dist-multinomial-link-logit/m-p/712124#M34435</guid>
      <dc:creator>tlse31</dc:creator>
      <dc:date>2021-01-18T14:38:00Z</dc:date>
    </item>
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