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    <title>topic Re: GLIMMIX and pseudo R-squares in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/GLIMMIX-and-pseudo-R-squares/m-p/35550#M1491</link>
    <description>The only way I can get numbers like R-squared is to output the residual values to a data set and then calculate R-squared from those.</description>
    <pubDate>Thu, 18 Nov 2010 13:20:09 GMT</pubDate>
    <dc:creator>Paige</dc:creator>
    <dc:date>2010-11-18T13:20:09Z</dc:date>
    <item>
      <title>GLIMMIX and pseudo R-squares</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/GLIMMIX-and-pseudo-R-squares/m-p/35549#M1490</link>
      <description>Hi all,&lt;BR /&gt;
&lt;BR /&gt;
Is there any way to calculate the pseudo R-squares with a GLIMMIX procedure?&lt;BR /&gt;
&lt;BR /&gt;
Regards,</description>
      <pubDate>Thu, 18 Nov 2010 09:06:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/GLIMMIX-and-pseudo-R-squares/m-p/35549#M1490</guid>
      <dc:creator>deleted_user</dc:creator>
      <dc:date>2010-11-18T09:06:46Z</dc:date>
    </item>
    <item>
      <title>Re: GLIMMIX and pseudo R-squares</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/GLIMMIX-and-pseudo-R-squares/m-p/35550#M1491</link>
      <description>The only way I can get numbers like R-squared is to output the residual values to a data set and then calculate R-squared from those.</description>
      <pubDate>Thu, 18 Nov 2010 13:20:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/GLIMMIX-and-pseudo-R-squares/m-p/35550#M1491</guid>
      <dc:creator>Paige</dc:creator>
      <dc:date>2010-11-18T13:20:09Z</dc:date>
    </item>
    <item>
      <title>Re: GLIMMIX and pseudo R-squares</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/GLIMMIX-and-pseudo-R-squares/m-p/35551#M1492</link>
      <description>When there are multiple random-effect terms in a model, the simple concept of the R^2 breaks down. That is, there is no natural or unambiguous concept of the usual R^2 with two or more variance-covariance terms in a model. Various authors have proposed R^2-TYPE statistics, based on either the marginal or conditional residuals, or based on differences of log-likelihoods. I suggest you read Liu et al. 2008. J. Appl. Stat. 35:1081-1092, or Vonesh et al. 1996. Biometrics 52:572-587. One has to calculate these brute-force with SAS, by first outputting the residuals into a data file.</description>
      <pubDate>Fri, 19 Nov 2010 14:34:03 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/GLIMMIX-and-pseudo-R-squares/m-p/35551#M1492</guid>
      <dc:creator>lvm</dc:creator>
      <dc:date>2010-11-19T14:34:03Z</dc:date>
    </item>
    <item>
      <title>Re: GLIMMIX and pseudo R-squares</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/GLIMMIX-and-pseudo-R-squares/m-p/35552#M1493</link>
      <description>Thank you LVM and paige !</description>
      <pubDate>Mon, 22 Nov 2010 12:11:39 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/GLIMMIX-and-pseudo-R-squares/m-p/35552#M1493</guid>
      <dc:creator>deleted_user</dc:creator>
      <dc:date>2010-11-22T12:11:39Z</dc:date>
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