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    <title>topic Model Comparison Questions in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Model-Comparison-Questions/m-p/13224#M221</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I used polynomial distribution lag (PDL) models to analyze the population of insect.&lt;/P&gt;&lt;P&gt;In the PDL model, the record with missing data will be ignored so the observation of dependent variable will be a little different.&lt;/P&gt;&lt;P&gt;For example: MODEL (1) Y=A + B + C&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; MODEL (2) Y=D + E + F&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;If there is no missing data, I can use AIC, RMSE, or Total R-Square to compare the model performence.&lt;/P&gt;&lt;P&gt;However, in the model (1), the A variable has some missing data so the observation number of Y will be fewer than model (2)&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Under this situation, is RMSE OK to compare the model performence?&amp;nbsp; &lt;/P&gt;&lt;P&gt;Thanks in advance...&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Tue, 20 Sep 2011 21:55:46 GMT</pubDate>
    <dc:creator>buski</dc:creator>
    <dc:date>2011-09-20T21:55:46Z</dc:date>
    <item>
      <title>Model Comparison Questions</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Model-Comparison-Questions/m-p/13224#M221</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I used polynomial distribution lag (PDL) models to analyze the population of insect.&lt;/P&gt;&lt;P&gt;In the PDL model, the record with missing data will be ignored so the observation of dependent variable will be a little different.&lt;/P&gt;&lt;P&gt;For example: MODEL (1) Y=A + B + C&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; MODEL (2) Y=D + E + F&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;If there is no missing data, I can use AIC, RMSE, or Total R-Square to compare the model performence.&lt;/P&gt;&lt;P&gt;However, in the model (1), the A variable has some missing data so the observation number of Y will be fewer than model (2)&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Under this situation, is RMSE OK to compare the model performence?&amp;nbsp; &lt;/P&gt;&lt;P&gt;Thanks in advance...&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 20 Sep 2011 21:55:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Model-Comparison-Questions/m-p/13224#M221</guid>
      <dc:creator>buski</dc:creator>
      <dc:date>2011-09-20T21:55:46Z</dc:date>
    </item>
    <item>
      <title>Model Comparison Questions</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Model-Comparison-Questions/m-p/13225#M222</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Why not limit to only cases that are in both models for consistency? &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;You can also compare the model estimates and RMSE for the model and then without the observations it would lose by this method to see the effect. &lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 20 Sep 2011 23:24:54 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Model-Comparison-Questions/m-p/13225#M222</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2011-09-20T23:24:54Z</dc:date>
    </item>
    <item>
      <title>Model Comparison Questions</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Model-Comparison-Questions/m-p/13226#M223</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;If I limit to only cases with no missing data, I will lost many observations in MODEL(2).&lt;/P&gt;&lt;P&gt;That's why I am wondering which estimates is appropriate to compare two models if I don't delete any obs in MODEL (2).&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I have data of mutiple years so I will do cross validation year by year.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 21 Sep 2011 14:29:18 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Model-Comparison-Questions/m-p/13226#M223</guid>
      <dc:creator>buski</dc:creator>
      <dc:date>2011-09-21T14:29:18Z</dc:date>
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