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    <title>topic Re: Proc NLIN and adjusted R² in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-and-adjusted-R/m-p/283020#M14911</link>
    <description>&lt;P&gt;Adjusted R-square is adjusted for the number of parameters fitted, &lt;U&gt;not&lt;/U&gt; for the absence of an intercept. Removing the intercept changes the definition of R-square by adding the assumption that in the absence of independent variable effects, the response would be zero (instead of some mean value). Although removing the intercept is sometimes convenient to get some&amp;nbsp;estimates, it is not compatible with estimating the &lt;EM&gt;proportion of variance explained&lt;/EM&gt; by your model.&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Fri, 08 Jul 2016 18:59:27 GMT</pubDate>
    <dc:creator>PGStats</dc:creator>
    <dc:date>2016-07-08T18:59:27Z</dc:date>
    <item>
      <title>Proc NLIN and adjusted R²</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-and-adjusted-R/m-p/282908#M14902</link>
      <description>&lt;P&gt;Hello everyone, I used a Proc NLIN to fit&amp;nbsp;a nonlinear function, but as this regression has no intercept, I have no R². I think, in this case, the adjusted R² is used [R²a = 1-SS (residuel) / SS (corrected total)], (mentioned in several publications). is anybody can help me to calculate it.&lt;/P&gt;</description>
      <pubDate>Fri, 08 Jul 2016 11:09:03 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-and-adjusted-R/m-p/282908#M14902</guid>
      <dc:creator>soumri</dc:creator>
      <dc:date>2016-07-08T11:09:03Z</dc:date>
    </item>
    <item>
      <title>Re: Proc NLIN and adjusted R²</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-and-adjusted-R/m-p/283020#M14911</link>
      <description>&lt;P&gt;Adjusted R-square is adjusted for the number of parameters fitted, &lt;U&gt;not&lt;/U&gt; for the absence of an intercept. Removing the intercept changes the definition of R-square by adding the assumption that in the absence of independent variable effects, the response would be zero (instead of some mean value). Although removing the intercept is sometimes convenient to get some&amp;nbsp;estimates, it is not compatible with estimating the &lt;EM&gt;proportion of variance explained&lt;/EM&gt; by your model.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 08 Jul 2016 18:59:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-and-adjusted-R/m-p/283020#M14911</guid>
      <dc:creator>PGStats</dc:creator>
      <dc:date>2016-07-08T18:59:27Z</dc:date>
    </item>
    <item>
      <title>Re: Proc NLIN and adjusted R²</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-and-adjusted-R/m-p/283261#M14936</link>
      <description>&lt;P&gt;&lt;SPAN&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/462"&gt;@PGStats﻿&lt;/a&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;Thank you very much PGstats for wealthy enough information that you have provided me, in addition, there is a fairly long conversation entitled "Adjusted R^2 (adjusted R square)" &amp;nbsp;which contains the answer to my question with further details.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 11 Jul 2016 09:01:54 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-and-adjusted-R/m-p/283261#M14936</guid>
      <dc:creator>soumri</dc:creator>
      <dc:date>2016-07-11T09:01:54Z</dc:date>
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