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    <title>topic Re: Stepwise regression &amp;quot;match&amp;quot; in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Stepwise-regression-quot-match-quot/m-p/409396#M65919</link>
    <description>&lt;P&gt;I'll take a crack at this, but it would help if you attach a snapshot of the data file.&amp;nbsp; It appears that your variable Sem. fab was grouped by JMP into two bins - some of the values were assigned +1 and others -1.&amp;nbsp; I believe the stepwise model will group a nominal variable, according to groups that work "best" in the model, so this variable appears to have been split into two groups.&amp;nbsp; That is fine, if Sem. fab is really a nominal variable (I'm guessing it refers to two designated groups of manufactured parts, for example).&amp;nbsp; Since it has numeric values, I'm not sure - and if it really is a continuous measure, then you should change the data type and model it that way.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Assuming it is a nominal variable, then you model is simply estimating 2 constant values - one for one of the groups and another for the other group.&amp;nbsp; So, your model is predicting the intercept +/- and constant value, depending on which group it is in.&amp;nbsp; This suggests to me that a stepwise regression is not the most useful way to look at this data.&amp;nbsp; I'd suggest doing some more exploratory graphical analysis, since there appear to be 2 groups of observations, each with a predicted value.&amp;nbsp; Are there no other explanatory variables for you to model?&amp;nbsp; With 2 predicted continuous outcomes, and 1 nominal variable (identifying the 2 groups of observations), a simple t test may suffice.&lt;/P&gt;</description>
    <pubDate>Fri, 13 Aug 2021 12:01:35 GMT</pubDate>
    <dc:creator>dale_lehman</dc:creator>
    <dc:date>2021-08-13T12:01:35Z</dc:date>
    <item>
      <title>Stepwise regression "match"</title>
      <link>https://community.jmp.com/t5/Discussions/Stepwise-regression-quot-match-quot/m-p/409349#M65913</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have a stepwise regression and I have the following results when I save the model in the database :&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Emma1_0-1628839582828.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/34988i901E2C05EF2D33AE/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Emma1_0-1628839582828.png" alt="Emma1_0-1628839582828.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Emma1_1-1628839616126.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/34989i3B2F464830C42D58/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Emma1_1-1628839616126.png" alt="Emma1_1-1628839616126.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;What does that mean ? Indeed, I have several coefficients for the same modality in a variable and it makes me "match". For example the modality "39" has 2 coefficients, "1" and "-1"&lt;BR /&gt;What are the "match"?&lt;BR /&gt;Thank you for your help&lt;/P&gt;</description>
      <pubDate>Fri, 09 Jun 2023 00:37:34 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Stepwise-regression-quot-match-quot/m-p/409349#M65913</guid>
      <dc:creator>Emma1</dc:creator>
      <dc:date>2023-06-09T00:37:34Z</dc:date>
    </item>
    <item>
      <title>Re: Stepwise regression "match"</title>
      <link>https://community.jmp.com/t5/Discussions/Stepwise-regression-quot-match-quot/m-p/409396#M65919</link>
      <description>&lt;P&gt;I'll take a crack at this, but it would help if you attach a snapshot of the data file.&amp;nbsp; It appears that your variable Sem. fab was grouped by JMP into two bins - some of the values were assigned +1 and others -1.&amp;nbsp; I believe the stepwise model will group a nominal variable, according to groups that work "best" in the model, so this variable appears to have been split into two groups.&amp;nbsp; That is fine, if Sem. fab is really a nominal variable (I'm guessing it refers to two designated groups of manufactured parts, for example).&amp;nbsp; Since it has numeric values, I'm not sure - and if it really is a continuous measure, then you should change the data type and model it that way.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Assuming it is a nominal variable, then you model is simply estimating 2 constant values - one for one of the groups and another for the other group.&amp;nbsp; So, your model is predicting the intercept +/- and constant value, depending on which group it is in.&amp;nbsp; This suggests to me that a stepwise regression is not the most useful way to look at this data.&amp;nbsp; I'd suggest doing some more exploratory graphical analysis, since there appear to be 2 groups of observations, each with a predicted value.&amp;nbsp; Are there no other explanatory variables for you to model?&amp;nbsp; With 2 predicted continuous outcomes, and 1 nominal variable (identifying the 2 groups of observations), a simple t test may suffice.&lt;/P&gt;</description>
      <pubDate>Fri, 13 Aug 2021 12:01:35 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Stepwise-regression-quot-match-quot/m-p/409396#M65919</guid>
      <dc:creator>dale_lehman</dc:creator>
      <dc:date>2021-08-13T12:01:35Z</dc:date>
    </item>
    <item>
      <title>Re: Stepwise regression "match"</title>
      <link>https://community.jmp.com/t5/Discussions/Stepwise-regression-quot-match-quot/m-p/409403#M65920</link>
      <description>&lt;P&gt;Here is a sample file I want to make a logistic regression model to predict the "Quality" variable representing the quality of cheeses.&lt;/P&gt;&lt;P&gt;In the example, I only put 6 variables but actually there is much more.&lt;/P&gt;&lt;P&gt;Before making my logistic regression model, I wanted to make a stepwise regression in order to select the best variables to integrate them into my model&lt;/P&gt;&lt;P&gt;However, I don't understand why it separates me into several groups the Variable Year, Month and Week&lt;/P&gt;&lt;P&gt;Indeed, these can not be continuous digital variables, they are in the correct format: ordinal digital&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks for your help&lt;/P&gt;</description>
      <pubDate>Fri, 13 Aug 2021 12:25:37 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Stepwise-regression-quot-match-quot/m-p/409403#M65920</guid>
      <dc:creator>Emma1</dc:creator>
      <dc:date>2021-08-13T12:25:37Z</dc:date>
    </item>
    <item>
      <title>Re: Stepwise regression "match"</title>
      <link>https://community.jmp.com/t5/Discussions/Stepwise-regression-quot-match-quot/m-p/409503#M65925</link>
      <description>&lt;P&gt;I'd suggest using Predictor Screening (under the Screening platform) to explore the various predictors.&amp;nbsp; I believe Stepwise will automatically group "similar" nominal variable values together (when they have similar impacts on the response variable), which is what I think you are seeing.&amp;nbsp; That can be useful when a nominal variable has a lot of levels, and there are groups of levels that have similar impacts.&amp;nbsp; But, from my experience, it makes it harder to see the importance of the different potential explanatory variables, so I'd start with predictor screening.&lt;/P&gt;</description>
      <pubDate>Fri, 13 Aug 2021 14:59:33 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Stepwise-regression-quot-match-quot/m-p/409503#M65925</guid>
      <dc:creator>dale_lehman</dc:creator>
      <dc:date>2021-08-13T14:59:33Z</dc:date>
    </item>
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