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    <title>topic Re: Missing data in mixed models in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Missing-data-in-mixed-models/m-p/256757#M13559</link>
    <description>&lt;P&gt;Thank you for your help!&lt;/P&gt;</description>
    <pubDate>Tue, 15 Mar 2016 13:32:07 GMT</pubDate>
    <dc:creator>mmraja</dc:creator>
    <dc:date>2016-03-15T13:32:07Z</dc:date>
    <item>
      <title>Missing data in mixed models</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Missing-data-in-mixed-models/m-p/254980#M13455</link>
      <description>&lt;P&gt;Hi all,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I was wondering where I could find information on how both PROC MIXED and PROC NLMIXED deal with missing data. Do they assume MAR? Do they have the same approach to dealing with missing data?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;When I run mixed models in both procs, the output includes "Number of Observations Read" and "Number of Observations Used," so I want to understand what is going on under the hood with both of these procs.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Any help woud be greatly appreciated!&lt;/P&gt;
&lt;P&gt;Thanks!!&lt;/P&gt;</description>
      <pubDate>Mon, 07 Mar 2016 16:21:56 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Missing-data-in-mixed-models/m-p/254980#M13455</guid>
      <dc:creator>mmraja</dc:creator>
      <dc:date>2016-03-07T16:21:56Z</dc:date>
    </item>
    <item>
      <title>Re: Missing data in mixed models</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Missing-data-in-mixed-models/m-p/256751#M13557</link>
      <description>&lt;P&gt;The online documentation states:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/viewer.htm#statug_mixed_details13.htm" target="_blank"&gt;http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/viewer.htm#statug_mixed_details13.htm&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;DIV class="xis-title"&gt;
&lt;DIV&gt;
&lt;DIV&gt;
&lt;H4 class="xis-title"&gt;Missing Level Combinations&lt;/H4&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;P&gt;PROC MIXED handles missing level combinations of classification variables similarly to the way PROC GLM does. Both procedures delete fixed-effects parameters corresponding to missing levels in order to preserve estimability. However, PROC MIXED does not delete missing level combinations for random-effects parameters because linear combinations of the random-effects parameters are always estimable. These conventions can affect the way you specify your &lt;A href="http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/statug_mixed_syntax05.htm" target="_blank"&gt;CONTRAST&lt;/A&gt; and &lt;A href="http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/statug_mixed_syntax06.htm" target="_blank"&gt;ESTIMATE&lt;/A&gt; coefficients.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You might consider multiple imputation if you have missing data. &amp;nbsp;SAS has the MI procedure.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;HTH,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Kevin&lt;/P&gt;</description>
      <pubDate>Tue, 15 Mar 2016 12:35:44 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Missing-data-in-mixed-models/m-p/256751#M13557</guid>
      <dc:creator>KevinViel</dc:creator>
      <dc:date>2016-03-15T12:35:44Z</dc:date>
    </item>
    <item>
      <title>Re: Missing data in mixed models</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Missing-data-in-mixed-models/m-p/256757#M13559</link>
      <description>&lt;P&gt;Thank you for your help!&lt;/P&gt;</description>
      <pubDate>Tue, 15 Mar 2016 13:32:07 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Missing-data-in-mixed-models/m-p/256757#M13559</guid>
      <dc:creator>mmraja</dc:creator>
      <dc:date>2016-03-15T13:32:07Z</dc:date>
    </item>
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