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    <title>topic Re: How DOE analysis handle categorical factor in regression analysis in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/How-DOE-analysis-handle-categorical-factor-in-regression/m-p/661599#M85031</link>
    <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/16303"&gt;@dadawasozo&lt;/a&gt;,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;There might be different encoding for categorical variables depending on which platform you're using.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;UL&gt;
&lt;LI&gt;For "Fit Model" (Standard Least Squares) approach :&amp;nbsp;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;"&lt;EM&gt;When you enter a column with a nominal modeling type in the Fit Model launch window, JMP represents it internally as a set of continuous indicator variables. Each variable assumes only the values –1, 0, and 1. (Note that this coding is one of many ways to use indicator variables to code nominal variables.) If your nominal column has&amp;nbsp;&lt;SPAN class="EquationVariables"&gt;n&lt;/SPAN&gt;&amp;nbsp;levels, then&amp;nbsp;&lt;SPAN class="EquationVariables"&gt;n&lt;/SPAN&gt;–1 of these indicator variables are needed to represent it. (The need for&amp;nbsp;&lt;SPAN class="EquationVariables"&gt;n&lt;/SPAN&gt;–1 indicator variables relates directly to the fact that the main effect associated with the nominal column has&amp;nbsp;&lt;SPAN class="EquationVariables"&gt;n&lt;/SPAN&gt;–1 degrees of freedom.) Full details are covered in&amp;nbsp;&lt;A title="Nominal Factors" href="https://www.jmp.com/support/help/en/17.1/jmp/nominal-factors.shtml#ww65535" target="_blank" rel="noopener noreferrer"&gt;Nominal Factors&lt;/A&gt;&lt;/EM&gt;&lt;SPAN&gt;&lt;EM&gt;.&lt;/EM&gt;"&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;From :&amp;nbsp;&lt;A href="https://www.jmp.com/support/help/en/17.1/#page/jmp/statistical-details-for-nominal-effects-coding.shtml#ww1047389" target="_blank" rel="noopener noreferrer"&gt;Statistical Details for Nominal Effects Coding&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;UL&gt;
&lt;LI&gt;For "Generalized Regression" (Standard Least Squares or other estimation methods) :&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;"&lt;EM&gt;The parameterization of nominal variables used in the Generalized Regression personality differs from their parameterization using other Fit Model personalities. The Generalized Regression personality uses indicator function parameterization. In this parameterization, the estimate that corresponds to the indicator for a level of a nominal variable is an estimate of the difference between the mean response at that level and the mean response at the last level. The last level is the level with the highest value order coding; it is the level whose indicator function is not included in the model."&lt;/EM&gt;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://www.jmp.com/support/help/en/17.1/#page/jmp/launch-the-generalized-regression-personality.shtml#" target="_blank" rel="noopener noreferrer"&gt;From :&amp;nbsp; Launch the Generalized Regression Personality&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You might be interested in this discussion where the differences between the platforms are investigated (differences in estimates, p-values of effects, ... between Fit Model and Generalized Regression platforms) :&amp;nbsp;&lt;A href="https://community.jmp.com/t5/Discussions/Random-effect-test/m-p/659523#M84878" target="_blank"&gt;https://community.jmp.com/t5/Discussions/Random-effect-test/m-p/659523#M84878&lt;/A&gt;&amp;nbsp;&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, 24 Jul 2023 07:03:02 GMT</pubDate>
    <dc:creator>Victor_G</dc:creator>
    <dc:date>2023-07-24T07:03:02Z</dc:date>
    <item>
      <title>How DOE analysis handle categorical factor in regression analysis</title>
      <link>https://community.jmp.com/t5/Discussions/How-DOE-analysis-handle-categorical-factor-in-regression/m-p/661542#M85027</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I use the DOE on categorical factors. the predicted formula is linear regression. I wonder how does the categorical factor handled and so the linear regression will work. is there any recoding on categorical factors? Can someone point me to related documentation how JMP handles that?&lt;/P&gt;</description>
      <pubDate>Mon, 24 Jul 2023 01:50:04 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/How-DOE-analysis-handle-categorical-factor-in-regression/m-p/661542#M85027</guid>
      <dc:creator>dadawasozo</dc:creator>
      <dc:date>2023-07-24T01:50:04Z</dc:date>
    </item>
    <item>
      <title>Re: How DOE analysis handle categorical factor in regression analysis</title>
      <link>https://community.jmp.com/t5/Discussions/How-DOE-analysis-handle-categorical-factor-in-regression/m-p/661599#M85031</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/16303"&gt;@dadawasozo&lt;/a&gt;,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;There might be different encoding for categorical variables depending on which platform you're using.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;UL&gt;
&lt;LI&gt;For "Fit Model" (Standard Least Squares) approach :&amp;nbsp;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;"&lt;EM&gt;When you enter a column with a nominal modeling type in the Fit Model launch window, JMP represents it internally as a set of continuous indicator variables. Each variable assumes only the values –1, 0, and 1. (Note that this coding is one of many ways to use indicator variables to code nominal variables.) If your nominal column has&amp;nbsp;&lt;SPAN class="EquationVariables"&gt;n&lt;/SPAN&gt;&amp;nbsp;levels, then&amp;nbsp;&lt;SPAN class="EquationVariables"&gt;n&lt;/SPAN&gt;–1 of these indicator variables are needed to represent it. (The need for&amp;nbsp;&lt;SPAN class="EquationVariables"&gt;n&lt;/SPAN&gt;–1 indicator variables relates directly to the fact that the main effect associated with the nominal column has&amp;nbsp;&lt;SPAN class="EquationVariables"&gt;n&lt;/SPAN&gt;–1 degrees of freedom.) Full details are covered in&amp;nbsp;&lt;A title="Nominal Factors" href="https://www.jmp.com/support/help/en/17.1/jmp/nominal-factors.shtml#ww65535" target="_blank" rel="noopener noreferrer"&gt;Nominal Factors&lt;/A&gt;&lt;/EM&gt;&lt;SPAN&gt;&lt;EM&gt;.&lt;/EM&gt;"&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;From :&amp;nbsp;&lt;A href="https://www.jmp.com/support/help/en/17.1/#page/jmp/statistical-details-for-nominal-effects-coding.shtml#ww1047389" target="_blank" rel="noopener noreferrer"&gt;Statistical Details for Nominal Effects Coding&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;UL&gt;
&lt;LI&gt;For "Generalized Regression" (Standard Least Squares or other estimation methods) :&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;"&lt;EM&gt;The parameterization of nominal variables used in the Generalized Regression personality differs from their parameterization using other Fit Model personalities. The Generalized Regression personality uses indicator function parameterization. In this parameterization, the estimate that corresponds to the indicator for a level of a nominal variable is an estimate of the difference between the mean response at that level and the mean response at the last level. The last level is the level with the highest value order coding; it is the level whose indicator function is not included in the model."&lt;/EM&gt;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://www.jmp.com/support/help/en/17.1/#page/jmp/launch-the-generalized-regression-personality.shtml#" target="_blank" rel="noopener noreferrer"&gt;From :&amp;nbsp; Launch the Generalized Regression Personality&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You might be interested in this discussion where the differences between the platforms are investigated (differences in estimates, p-values of effects, ... between Fit Model and Generalized Regression platforms) :&amp;nbsp;&lt;A href="https://community.jmp.com/t5/Discussions/Random-effect-test/m-p/659523#M84878" target="_blank"&gt;https://community.jmp.com/t5/Discussions/Random-effect-test/m-p/659523#M84878&lt;/A&gt;&amp;nbsp;&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, 24 Jul 2023 07:03:02 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/How-DOE-analysis-handle-categorical-factor-in-regression/m-p/661599#M85031</guid>
      <dc:creator>Victor_G</dc:creator>
      <dc:date>2023-07-24T07:03:02Z</dc:date>
    </item>
    <item>
      <title>Re: How DOE analysis handle categorical factor in regression analysis</title>
      <link>https://community.jmp.com/t5/Discussions/How-DOE-analysis-handle-categorical-factor-in-regression/m-p/661713#M85047</link>
      <description>&lt;P&gt;Hi Victor,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks a lot for the reply. These information definitely helpful.&lt;/P&gt;</description>
      <pubDate>Mon, 24 Jul 2023 12:11:49 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/How-DOE-analysis-handle-categorical-factor-in-regression/m-p/661713#M85047</guid>
      <dc:creator>dadawasozo</dc:creator>
      <dc:date>2023-07-24T12:11:49Z</dc:date>
    </item>
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