<?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: 4-level mixed effects model with binary outcome in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/4-level-mixed-effects-model-with-binary-outcome/m-p/325112#M17168</link>
    <description>&lt;P&gt;This should be as simple as:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc glimmix data=yourdata;
class A B C &amp;lt;fixed effects&amp;gt; ;
model &amp;lt;response&amp;gt; = &amp;lt;fixed effects&amp;gt;/dist=binomial;
random intercept B B*C/subject=A;
run;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;Here everything in angle brackets is up for grabs, without greater detail for the design. &amp;nbsp;The RANDOM statement is written in intercept form to improve convergence properties.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Try filling in the angle brackets, and seeing how this works.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Steve Denham&lt;/P&gt;</description>
    <pubDate>Mon, 16 Jan 2017 19:48:53 GMT</pubDate>
    <dc:creator>SteveDenham</dc:creator>
    <dc:date>2017-01-16T19:48:53Z</dc:date>
    <item>
      <title>4-level mixed effects model with binary outcome</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/4-level-mixed-effects-model-with-binary-outcome/m-p/323860#M17112</link>
      <description>Hi All,&lt;BR /&gt;&lt;BR /&gt;Does anyone know how to model 4-level clustered data with binary outcome using proc glimmix or any other proc?&lt;BR /&gt;&lt;BR /&gt;The data has 3 nested clusters like this：A(B(C(level 1 events))).&lt;BR /&gt;&lt;BR /&gt;Any help is much appreciated!</description>
      <pubDate>Wed, 11 Jan 2017 06:36:33 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/4-level-mixed-effects-model-with-binary-outcome/m-p/323860#M17112</guid>
      <dc:creator>AprilS</dc:creator>
      <dc:date>2017-01-11T06:36:33Z</dc:date>
    </item>
    <item>
      <title>Re: 4-level mixed effects model with binary outcome</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/4-level-mixed-effects-model-with-binary-outcome/m-p/325112#M17168</link>
      <description>&lt;P&gt;This should be as simple as:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc glimmix data=yourdata;
class A B C &amp;lt;fixed effects&amp;gt; ;
model &amp;lt;response&amp;gt; = &amp;lt;fixed effects&amp;gt;/dist=binomial;
random intercept B B*C/subject=A;
run;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;Here everything in angle brackets is up for grabs, without greater detail for the design. &amp;nbsp;The RANDOM statement is written in intercept form to improve convergence properties.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Try filling in the angle brackets, and seeing how this works.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Steve Denham&lt;/P&gt;</description>
      <pubDate>Mon, 16 Jan 2017 19:48:53 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/4-level-mixed-effects-model-with-binary-outcome/m-p/325112#M17168</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2017-01-16T19:48:53Z</dc:date>
    </item>
  </channel>
</rss>

