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    <title>topic Re: Multivariate regression with or without intercept in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/395164#M20630</link>
    <description>Miller: Its good idea to see if the intercept is not statistically different from zero. How do you check for non-linearity?</description>
    <pubDate>Tue, 12 Sep 2017 16:49:44 GMT</pubDate>
    <dc:creator>CheerfulChu</dc:creator>
    <dc:date>2017-09-12T16:49:44Z</dc:date>
    <item>
      <title>Multivariate regression with or without intercept</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/384684#M20007</link>
      <description>&lt;P&gt;Dear Experts,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I have a multivariate model,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Y ~ X1 + X2 + X3 + X4 + X5 + X6 + intercept(?)&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I read that it is better to keep the intercept else the regession line will be biased especially it is forced to go through the origin with 6 variables in the equation above.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;However, in the legacy program, the intercept is removed and externally studentized residuals are calculated. Would you keep or dont keep the intercept and why so?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Thank you&lt;/P&gt;
&lt;P&gt;LL&lt;/P&gt;</description>
      <pubDate>Tue, 01 Aug 2017 17:11:04 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/384684#M20007</guid>
      <dc:creator>CheerfulChu</dc:creator>
      <dc:date>2017-08-01T17:11:04Z</dc:date>
    </item>
    <item>
      <title>Re: Multivariate regression with or without intercept</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/384686#M20008</link>
      <description>&lt;P&gt;Context matters. It depends a bit on what type of model and your subject area. In certain cases this approach makes sense and in others it doesn't. I don't believe we have enough information to actually answer your question.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 01 Aug 2017 17:14:25 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/384686#M20008</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2017-08-01T17:14:25Z</dc:date>
    </item>
    <item>
      <title>Re: Multivariate regression with or without intercept</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/384707#M20010</link>
      <description>&lt;P&gt;It's hard for me to think of a good reason to leave the intercept out.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Even in the famous example of adding soap to water and measuring the amount of suds created, you would expect zero soap to produce zero suds ... a true statement ...&amp;nbsp;but that's not the right thought process. If you are measuring the process near zero on the x-axis (near zero soap) you may find the process to be non-linear and it curves through the origin, in which case a linear regression is not appropriate; and if you are measuring the process away from zero on the x-axis (far away from zero soap) then you may find a linear model fits well in that region of the x-axis,&amp;nbsp;but the model does not go through the origin.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;In any case, I would certainly include the intercept in the model, and test to see if the intercept is not statistically different from zero before excluding the intercept. I would also check the data for non-linearity.&lt;/P&gt;</description>
      <pubDate>Tue, 01 Aug 2017 18:28:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/384707#M20010</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2017-08-01T18:28:27Z</dc:date>
    </item>
    <item>
      <title>Re: Multivariate regression with or without intercept</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/395164#M20630</link>
      <description>Miller: Its good idea to see if the intercept is not statistically different from zero. How do you check for non-linearity?</description>
      <pubDate>Tue, 12 Sep 2017 16:49:44 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/395164#M20630</guid>
      <dc:creator>CheerfulChu</dc:creator>
      <dc:date>2017-09-12T16:49:44Z</dc:date>
    </item>
    <item>
      <title>Re: Multivariate regression with or without intercept</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/395173#M20632</link>
      <description>&lt;P&gt;Check for non-linearity by examining the residuals from a linear model fit.&lt;/P&gt;</description>
      <pubDate>Tue, 12 Sep 2017 17:21:13 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Multivariate-regression-with-or-without-intercept/m-p/395173#M20632</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2017-09-12T17:21:13Z</dc:date>
    </item>
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