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    <title>topic How to test the assumptions of proc MIXED? in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-test-the-assumptions-of-proc-MIXED/m-p/278795#M14721</link>
    <description>&lt;P&gt;Hello,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I run a proc MIXED on my data with a fixed factor (two infection status, InfStaStr = in, un) and some nested random factors (Stain=IsolStr=1,2,3,5 and Repeats per strain = IsolRepeatStr=A,B ...). The response is total fecundity, measured as number of eggs laid. I want to know if the infection status has an effect on total fecundity. I also want to know if the random factors are significant.The code is shown below:&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;PROC Mixed DATA = WORK.SORTTempTableSorted covtest&lt;BR /&gt; PLOTS(ONLY)=ALL&lt;BR /&gt; METHOD=REML;&lt;BR /&gt; CLASS IsolStr IsolRepeatStr InfStaStr;&lt;BR /&gt; MODEL TotalFecundity= InfStaStr / HTYPE=3 E3;&lt;BR /&gt; RANDOM IsolStr IsolRepeatStrain(IsolStr) / TYPE=VC;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I am&amp;nbsp;using SAS Enterprise Guide 7.1 (64-bit). I am attaching part of the output as a JPG file. The notes for the run do not indicate any problems (see attachment).&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I need help with testing the assumptions of the analysis. I am confused in part becasue some sources define the assumptions in different ways (they seem different to me):&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;For example,&amp;nbsp;The MIXED manual from SAS states the assumptions as follows:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;-The data are normally distributed (Gaussian).&lt;BR /&gt;-The means (expected values) of the data are linear in terms of a certain set of parameters.&lt;BR /&gt;-The variances and covariances of the data are in terms of a different set of parameters, and they exhibit a structure matching one of those available in PROC MIXED.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Another document, the one entitled "Heteroscedasticity under the linear mixed model" states the assumption as follows:&lt;/P&gt;
&lt;P&gt;- Normality of the random effects distribution;&lt;/P&gt;
&lt;P&gt;- Independency of the response given the random effects i.e. independency of the errors;&lt;/P&gt;
&lt;P&gt;- Normality of the error;&lt;/P&gt;
&lt;P&gt;- Homoscedasticity of the error.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;To make this matter more confusing to me, I have seen google searches from people asking for help to test for normality,&amp;nbsp;homoscedasticity, and outliers (influential values) after running proc MIXED. My questions are:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;What are the assumption to check after running proc MIXED?&lt;/P&gt;
&lt;P&gt;How to test those assumptions and where to find clear examples of such tests?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I will be very obliged to anyone who can help.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Regards,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;igforek&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;BR /&gt;&lt;IMG src="https://communities.sas.com/t5/image/serverpage/image-id/12674iE8A7E923A82F45DE/image-size/large?v=1.0&amp;amp;px=600" border="0" alt="SAS_To_Question.jpg" title="SAS_To_Question.jpg" /&gt;</description>
    <pubDate>Thu, 23 Jun 2016 15:01:46 GMT</pubDate>
    <dc:creator>igforek</dc:creator>
    <dc:date>2016-06-23T15:01:46Z</dc:date>
    <item>
      <title>How to test the assumptions of proc MIXED?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-test-the-assumptions-of-proc-MIXED/m-p/278795#M14721</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I run a proc MIXED on my data with a fixed factor (two infection status, InfStaStr = in, un) and some nested random factors (Stain=IsolStr=1,2,3,5 and Repeats per strain = IsolRepeatStr=A,B ...). The response is total fecundity, measured as number of eggs laid. I want to know if the infection status has an effect on total fecundity. I also want to know if the random factors are significant.The code is shown below:&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;PROC Mixed DATA = WORK.SORTTempTableSorted covtest&lt;BR /&gt; PLOTS(ONLY)=ALL&lt;BR /&gt; METHOD=REML;&lt;BR /&gt; CLASS IsolStr IsolRepeatStr InfStaStr;&lt;BR /&gt; MODEL TotalFecundity= InfStaStr / HTYPE=3 E3;&lt;BR /&gt; RANDOM IsolStr IsolRepeatStrain(IsolStr) / TYPE=VC;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I am&amp;nbsp;using SAS Enterprise Guide 7.1 (64-bit). I am attaching part of the output as a JPG file. The notes for the run do not indicate any problems (see attachment).&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I need help with testing the assumptions of the analysis. I am confused in part becasue some sources define the assumptions in different ways (they seem different to me):&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;For example,&amp;nbsp;The MIXED manual from SAS states the assumptions as follows:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;-The data are normally distributed (Gaussian).&lt;BR /&gt;-The means (expected values) of the data are linear in terms of a certain set of parameters.&lt;BR /&gt;-The variances and covariances of the data are in terms of a different set of parameters, and they exhibit a structure matching one of those available in PROC MIXED.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Another document, the one entitled "Heteroscedasticity under the linear mixed model" states the assumption as follows:&lt;/P&gt;
&lt;P&gt;- Normality of the random effects distribution;&lt;/P&gt;
&lt;P&gt;- Independency of the response given the random effects i.e. independency of the errors;&lt;/P&gt;
&lt;P&gt;- Normality of the error;&lt;/P&gt;
&lt;P&gt;- Homoscedasticity of the error.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;To make this matter more confusing to me, I have seen google searches from people asking for help to test for normality,&amp;nbsp;homoscedasticity, and outliers (influential values) after running proc MIXED. My questions are:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;What are the assumption to check after running proc MIXED?&lt;/P&gt;
&lt;P&gt;How to test those assumptions and where to find clear examples of such tests?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I will be very obliged to anyone who can help.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Regards,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;igforek&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;BR /&gt;&lt;IMG src="https://communities.sas.com/t5/image/serverpage/image-id/12674iE8A7E923A82F45DE/image-size/large?v=1.0&amp;amp;px=600" border="0" alt="SAS_To_Question.jpg" title="SAS_To_Question.jpg" /&gt;</description>
      <pubDate>Thu, 23 Jun 2016 15:01:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-test-the-assumptions-of-proc-MIXED/m-p/278795#M14721</guid>
      <dc:creator>igforek</dc:creator>
      <dc:date>2016-06-23T15:01:46Z</dc:date>
    </item>
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