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    <title>topic Re: Den df=0 in proc glimmix in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Den-df-0-in-proc-glimmix/m-p/183056#M9506</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I am guessing you have unbalanced data, with a lot of cells with no observations (in the three-way table). I usually see this problem with the default ddf method (ddfm=containment).&amp;nbsp; You could use ddfm=kr (for Kenward-Roger method). This will work for the default estimation method. However, the default estimation method is probably not the best choice for binary data because of bias of parameter estimates. I would suggest you use the option method=laplace on the procedure statement. But if you do that, you cannot use ddfm=kr.&amp;nbsp; If you felt you had enough observations, you could use chi-squared wald statistics instead of F statistics for hypothesis testing and confidence intervals. Just put CHISQ as an option in the model statement. &lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Thu, 17 Apr 2014 13:34:56 GMT</pubDate>
    <dc:creator>lvm</dc:creator>
    <dc:date>2014-04-17T13:34:56Z</dc:date>
    <item>
      <title>Den df=0 in proc glimmix</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Den-df-0-in-proc-glimmix/m-p/183055#M9505</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hello all,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I am using proc glimmix to fit a multilevel logistical model. Den df in the parameter estimates of gender*TE*item is 0 so there is no p value. What might be the reason?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc glimmix data=data1;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; class tID sID item gender TE;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; model response (Event='1')= item gender*TE*item / Dist=Binary link=logit solution noint&amp;nbsp; DDFM=BW;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; random intercept&amp;nbsp; / subject=tID type=vc;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; random intercept&amp;nbsp; / subject=sID(tID) type=vc;&lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 17 Apr 2014 03:47:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Den-df-0-in-proc-glimmix/m-p/183055#M9505</guid>
      <dc:creator>Yao_W</dc:creator>
      <dc:date>2014-04-17T03:47:46Z</dc:date>
    </item>
    <item>
      <title>Re: Den df=0 in proc glimmix</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Den-df-0-in-proc-glimmix/m-p/183056#M9506</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I am guessing you have unbalanced data, with a lot of cells with no observations (in the three-way table). I usually see this problem with the default ddf method (ddfm=containment).&amp;nbsp; You could use ddfm=kr (for Kenward-Roger method). This will work for the default estimation method. However, the default estimation method is probably not the best choice for binary data because of bias of parameter estimates. I would suggest you use the option method=laplace on the procedure statement. But if you do that, you cannot use ddfm=kr.&amp;nbsp; If you felt you had enough observations, you could use chi-squared wald statistics instead of F statistics for hypothesis testing and confidence intervals. Just put CHISQ as an option in the model statement. &lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 17 Apr 2014 13:34:56 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Den-df-0-in-proc-glimmix/m-p/183056#M9506</guid>
      <dc:creator>lvm</dc:creator>
      <dc:date>2014-04-17T13:34:56Z</dc:date>
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