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    <title>topic Re: Covariate as a designing factors in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Covariate-as-a-designing-factors/m-p/766327#M94641</link>
    <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/57587"&gt;@Sherif_96&lt;/a&gt;,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Yes, you can create a datatable with your covariates and list all their possible values.&lt;BR /&gt;Then, you can use the platform Custom design, and in the "Covariate / Candidate Runs" panel, click on "Select Covariate Factors" to select the covariate factors from your table :&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Victor_G_0-1718622733509.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/65273i85D0E4206720AD64/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Victor_G_0-1718622733509.png" alt="Victor_G_0-1718622733509.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Hope this answer will help you,&lt;/P&gt;</description>
    <pubDate>Mon, 17 Jun 2024 11:48:08 GMT</pubDate>
    <dc:creator>Victor_G</dc:creator>
    <dc:date>2024-06-17T11:48:08Z</dc:date>
    <item>
      <title>Covariate as a designing factors</title>
      <link>https://community.jmp.com/t5/Discussions/Covariate-as-a-designing-factors/m-p/766290#M94636</link>
      <description>If I already have an experiment with three inputs, can I add their data as a covariate in the custom design rather than specifying them as discrete or continuous variables and then designing an Experiment based on those three covariates only?</description>
      <pubDate>Mon, 17 Jun 2024 10:51:42 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Covariate-as-a-designing-factors/m-p/766290#M94636</guid>
      <dc:creator>Sherif_96</dc:creator>
      <dc:date>2024-06-17T10:51:42Z</dc:date>
    </item>
    <item>
      <title>Re: Covariate as a designing factors</title>
      <link>https://community.jmp.com/t5/Discussions/Covariate-as-a-designing-factors/m-p/766327#M94641</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/57587"&gt;@Sherif_96&lt;/a&gt;,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Yes, you can create a datatable with your covariates and list all their possible values.&lt;BR /&gt;Then, you can use the platform Custom design, and in the "Covariate / Candidate Runs" panel, click on "Select Covariate Factors" to select the covariate factors from your table :&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Victor_G_0-1718622733509.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/65273i85D0E4206720AD64/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Victor_G_0-1718622733509.png" alt="Victor_G_0-1718622733509.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Hope this answer will help you,&lt;/P&gt;</description>
      <pubDate>Mon, 17 Jun 2024 11:48:08 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Covariate-as-a-designing-factors/m-p/766327#M94641</guid>
      <dc:creator>Victor_G</dc:creator>
      <dc:date>2024-06-17T11:48:08Z</dc:date>
    </item>
    <item>
      <title>Re: Covariate as a designing factors</title>
      <link>https://community.jmp.com/t5/Discussions/Covariate-as-a-designing-factors/m-p/766381#M94646</link>
      <description>&lt;P&gt;Perhaps you are using another definition for a covariate, but covariates are meant to be measurable, &lt;STRONG&gt;uncontrollable&lt;/STRONG&gt; factors in an experiment. &amp;nbsp;Using covariates in an experiment is a way to handle noise that is measurable in the experiment. &amp;nbsp;The covariate is a random variable in an otherwise fixed effects model (hence mixed model). &amp;nbsp;Analysis of the covariate modifies the data to account for the covariate effect before analysis of the fixed effects model is done. &amp;nbsp;Depending on the size of the experiment, there is a limit to the number of covariates you can account for.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Now you can certainly do regression using random variables all you want.&lt;/P&gt;</description>
      <pubDate>Mon, 17 Jun 2024 13:59:02 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Covariate-as-a-designing-factors/m-p/766381#M94646</guid>
      <dc:creator>statman</dc:creator>
      <dc:date>2024-06-17T13:59:02Z</dc:date>
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