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    <title>topic Re: How to do glimmix model with nominal (unordered) outcome in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563812#M27827</link>
    <description>Thanks, the response just has 3 levels and I only used one predictor with 2&lt;BR /&gt;levels, the sample size is about 500. Then I guess it is just because of&lt;BR /&gt;the computer power? Besides the computer power, I am curious if there is&lt;BR /&gt;any statistical computation method which might help?&lt;BR /&gt;&lt;BR /&gt;Thanks again!</description>
    <pubDate>Wed, 05 Jun 2019 18:12:58 GMT</pubDate>
    <dc:creator>AprilS</dc:creator>
    <dc:date>2019-06-05T18:12:58Z</dc:date>
    <item>
      <title>How to do glimmix model with nominal (unordered) outcome?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563620#M27823</link>
      <description>&lt;P&gt;I am trying to fit a multinomial logistic model with random effects (ID is the cluster) and a 3-level nominal outcome, the outcome is not ordinal. I used SAS code like below:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;   proc glimmix;
      class ID outcome;
      model outcome(ref=first) = explanatory/
                      dist=multinomial 
                      link=glogit;
      random intercept / subject=ID group=outcome;
   run;&lt;/PRE&gt;&lt;P&gt;But the model did not work and said&amp;nbsp;G matrix is not positive definite. I tried glogit model several times with different outcomes and clusters, it either runs out of memory or has other issues. I wonder if I did anything wrong or there is a better way to do this kind of models in SAS?&lt;/P&gt;</description>
      <pubDate>Tue, 04 Jun 2019 23:31:57 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563620#M27823</guid>
      <dc:creator>AprilS</dc:creator>
      <dc:date>2019-06-04T23:31:57Z</dc:date>
    </item>
    <item>
      <title>Re: How to do glimmix model with nominal (unordered) outcome?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563731#M27824</link>
      <description>&lt;P&gt;You could instead try fitting a GEE model:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc gee;
      class ID;
      model outcome(ref=first) = explanatory/
                      dist=mult link=glogit;
      repeated subject=ID;
   run;&lt;/CODE&gt;&lt;/PRE&gt;</description>
      <pubDate>Wed, 05 Jun 2019 15:35:07 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563731#M27824</guid>
      <dc:creator>StatDave</dc:creator>
      <dc:date>2019-06-05T15:35:07Z</dc:date>
    </item>
    <item>
      <title>Re: How to do glimmix model with nominal (unordered) outcome?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563761#M27825</link>
      <description>&lt;P&gt;Thanks! I tried this too, but it runs forever. Not sure if it is because of my computer or this model is too complex?&amp;nbsp;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 05 Jun 2019 16:52:38 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563761#M27825</guid>
      <dc:creator>AprilS</dc:creator>
      <dc:date>2019-06-05T16:52:38Z</dc:date>
    </item>
    <item>
      <title>Re: How to do glimmix model with nominal (unordered) outcome?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563802#M27826</link>
      <description>&lt;P&gt;Like all modeling procedures, the time and memory needed increases with the number of parameters in the model. So, you might want to start with a small model (few predictors) and see if you can build up to a suitable model. Note that the number of parameters will increase dramatically as the number of levels of the response increases. So, if there are many response levels, you might consider a modified response that merges categories into fewer levels.&lt;/P&gt;</description>
      <pubDate>Wed, 05 Jun 2019 18:04:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563802#M27826</guid>
      <dc:creator>StatDave</dc:creator>
      <dc:date>2019-06-05T18:04:27Z</dc:date>
    </item>
    <item>
      <title>Re: How to do glimmix model with nominal (unordered) outcome</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563812#M27827</link>
      <description>Thanks, the response just has 3 levels and I only used one predictor with 2&lt;BR /&gt;levels, the sample size is about 500. Then I guess it is just because of&lt;BR /&gt;the computer power? Besides the computer power, I am curious if there is&lt;BR /&gt;any statistical computation method which might help?&lt;BR /&gt;&lt;BR /&gt;Thanks again!</description>
      <pubDate>Wed, 05 Jun 2019 18:12:58 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563812#M27827</guid>
      <dc:creator>AprilS</dc:creator>
      <dc:date>2019-06-05T18:12:58Z</dc:date>
    </item>
    <item>
      <title>Re: How to do glimmix model with nominal (unordered) outcome</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563815#M27828</link>
      <description>&lt;P&gt;So, you really just have an Sx2x3 table, where S is the number of subjects. For that, you can use a nonmodel-based approach. You could use the CMH statistics in PROC FREQ with your subject variable as the stratifying variable. For example, if your 2 level predictor is X and your 3 level response is Y:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc freq;
table s*x*y/cmh noprint;
run;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;The second CMH statistic tests if X and Y are associated. See the discussion in the FREQ documentation for details.&lt;/P&gt;</description>
      <pubDate>Wed, 05 Jun 2019 18:19:56 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-do-glimmix-model-with-nominal-unordered-outcome/m-p/563815#M27828</guid>
      <dc:creator>StatDave</dc:creator>
      <dc:date>2019-06-05T18:19:56Z</dc:date>
    </item>
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