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    <title>topic Re: Nested Effect Causes &amp;quot;Did not converge&amp;quot; Error in Proc Glimmix in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Nested-Effect-Causes-quot-Did-not-converge-quot-Error-in-Proc/m-p/716476#M34661</link>
    <description>&lt;P&gt;Please keep in mind each data set and model should be evaluated independently. Here are a few suggestions to try when you encounter the fail to converge message in the SAS LOG when using PROC GLIMMIX:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You can try some of the NLOPTIONS when you have convergence problems. For &lt;BR /&gt;example,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;NLOPTIONS TECHNIQUE=NRRIDG; or NLOPTIONS TECH=NEWRAP;&lt;/P&gt;
&lt;P&gt;and see if that helps your model to converge.&amp;nbsp;&amp;nbsp;Using NLOPTIONS=NRRIDG; for Binary, Binomial, Poisson, NegBin seems to help convergence.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;If your variables or parameter estimates are of wildly different scales (like .0001 vs 100) then you may need to rescale your data or your model.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Try different starting values for your random effects by adding a PARMS statement.&amp;nbsp;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You can also try adding the INITGLM option to the PROC GLIMIMX statement.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Examine the iteration history, does it look like it is making progress toward convergence. At the end (19 + 1initial optimizations is the default) if you are oh-so-close but do not quite make the convergence criteria. I would suggest that you&amp;nbsp;&amp;nbsp;increase the MAXOPT= in the PROC statement to 50 to see if your model converges. You can also increase the MAXITER= option on the NLOPTIONS statement to increase the number of iterations.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Try different METHODs= Laplace etc&amp;nbsp;&amp;nbsp;on PROC GLIMMIX statement such as METHOD=LAPLACE or QUAD if you are using SAS 9.2 or later for conditional model.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You may have to reconsider your model and simplify it.&amp;nbsp;&amp;nbsp;You may have to use simpler TYPE= structure as in your example TYPE=VC rather than TYPE=UN or you may have to reconsider the fixed effects.&lt;/P&gt;</description>
    <pubDate>Wed, 03 Feb 2021 15:05:29 GMT</pubDate>
    <dc:creator>STAT_Kathleen</dc:creator>
    <dc:date>2021-02-03T15:05:29Z</dc:date>
    <item>
      <title>Nested Effect Causes "Did not converge" Error in Proc Glimmix</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Nested-Effect-Causes-quot-Did-not-converge-quot-Error-in-Proc/m-p/704857#M34253</link>
      <description>&lt;P&gt;I'm using proc glimmix to analyze calves born and calves weaned but it gives me the error: "Data did not converge" when I have a nested variable in the model statement for calves born. The data is almost exactly the same for calves born and calves weaned, both are 0s and 1s with only a slight difference in the total amount of each between the variables, but for some reason proc glimmix will only converge my data for calves weaned with a nested variable. The models are exactly the same except for the dependent variable. They are:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;birthed_calfnum= f2_animal_breed cow_age(f2_animal_birth_year)&amp;nbsp;/ dist=binomial link=logit;&lt;/P&gt;&lt;P&gt;random f2_animal_id;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;and&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;weaned_calfnum= f2_animal_breed cow_age(f2_animal_birth_year)&amp;nbsp;/ dist=binomial link=logit;&lt;/P&gt;&lt;P&gt;random f2_animal_id;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I've tried just running the model with the nested effect and upping the number of iterations but I still get the same error message. Does anyone have any idea what's going on and how to fix it? Thank you!&lt;/P&gt;</description>
      <pubDate>Wed, 09 Dec 2020 20:21:41 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Nested-Effect-Causes-quot-Did-not-converge-quot-Error-in-Proc/m-p/704857#M34253</guid>
      <dc:creator>DanaM</dc:creator>
      <dc:date>2020-12-09T20:21:41Z</dc:date>
    </item>
    <item>
      <title>Re: Nested Effect Causes "Did not converge" Error in Proc Glimmix</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Nested-Effect-Causes-quot-Did-not-converge-quot-Error-in-Proc/m-p/716476#M34661</link>
      <description>&lt;P&gt;Please keep in mind each data set and model should be evaluated independently. Here are a few suggestions to try when you encounter the fail to converge message in the SAS LOG when using PROC GLIMMIX:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You can try some of the NLOPTIONS when you have convergence problems. For &lt;BR /&gt;example,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;NLOPTIONS TECHNIQUE=NRRIDG; or NLOPTIONS TECH=NEWRAP;&lt;/P&gt;
&lt;P&gt;and see if that helps your model to converge.&amp;nbsp;&amp;nbsp;Using NLOPTIONS=NRRIDG; for Binary, Binomial, Poisson, NegBin seems to help convergence.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;If your variables or parameter estimates are of wildly different scales (like .0001 vs 100) then you may need to rescale your data or your model.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Try different starting values for your random effects by adding a PARMS statement.&amp;nbsp;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You can also try adding the INITGLM option to the PROC GLIMIMX statement.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Examine the iteration history, does it look like it is making progress toward convergence. At the end (19 + 1initial optimizations is the default) if you are oh-so-close but do not quite make the convergence criteria. I would suggest that you&amp;nbsp;&amp;nbsp;increase the MAXOPT= in the PROC statement to 50 to see if your model converges. You can also increase the MAXITER= option on the NLOPTIONS statement to increase the number of iterations.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Try different METHODs= Laplace etc&amp;nbsp;&amp;nbsp;on PROC GLIMMIX statement such as METHOD=LAPLACE or QUAD if you are using SAS 9.2 or later for conditional model.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You may have to reconsider your model and simplify it.&amp;nbsp;&amp;nbsp;You may have to use simpler TYPE= structure as in your example TYPE=VC rather than TYPE=UN or you may have to reconsider the fixed effects.&lt;/P&gt;</description>
      <pubDate>Wed, 03 Feb 2021 15:05:29 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Nested-Effect-Causes-quot-Did-not-converge-quot-Error-in-Proc/m-p/716476#M34661</guid>
      <dc:creator>STAT_Kathleen</dc:creator>
      <dc:date>2021-02-03T15:05:29Z</dc:date>
    </item>
    <item>
      <title>Re: Nested Effect Causes "Did not converge" Error in Proc Glimmix</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Nested-Effect-Causes-quot-Did-not-converge-quot-Error-in-Proc/m-p/717462#M34692</link>
      <description>Thanks! I was able to get it to run using laplace</description>
      <pubDate>Sun, 07 Feb 2021 23:49:45 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Nested-Effect-Causes-quot-Did-not-converge-quot-Error-in-Proc/m-p/717462#M34692</guid>
      <dc:creator>DanaM</dc:creator>
      <dc:date>2021-02-07T23:49:45Z</dc:date>
    </item>
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