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    <title>topic Re: interpreting parameter estimates in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/interpreting-parameter-estimates/m-p/483913#M72827</link>
    <description>&lt;P&gt;I think that this case is a mixture experiment. so the intercept is present but not explicit.&lt;/P&gt;</description>
    <pubDate>Tue, 03 May 2022 15:54:25 GMT</pubDate>
    <dc:creator>Mark_Bailey</dc:creator>
    <dc:date>2022-05-03T15:54:25Z</dc:date>
    <item>
      <title>interpreting parameter estimates</title>
      <link>https://community.jmp.com/t5/Discussions/interpreting-parameter-estimates/m-p/483535#M72801</link>
      <description>&lt;P&gt;I have to determine what terms appear most dominant to the response based on the parameter estimates table. I am a little confused because of the negative coefficients for some of the terms under the estimate column.&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="parameter estimate hardness.jpg" style="width: 634px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/42178i9F583C9A2E0B6695/image-size/large?v=v2&amp;amp;px=999" role="button" title="parameter estimate hardness.jpg" alt="parameter estimate hardness.jpg" /&gt;&lt;/span&gt;&lt;/P&gt;</description>
      <pubDate>Sat, 10 Jun 2023 23:47:47 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/interpreting-parameter-estimates/m-p/483535#M72801</guid>
      <dc:creator>kenlynn2</dc:creator>
      <dc:date>2023-06-10T23:47:47Z</dc:date>
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    <item>
      <title>Re: interpreting parameter estimates</title>
      <link>https://community.jmp.com/t5/Discussions/interpreting-parameter-estimates/m-p/483861#M72818</link>
      <description>&lt;P&gt;The interaction terms represent an effect over and above the 'main effects,' 'linear effects,' or 'additive effects.' The negative parameter indicates an 'antagonistic' effect: this model predicts less of a positive change in the response than expected from the linear terms alone.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;It seems that some of the parameters are not significantly different from zero, so these terms can be eliminated. The best practice is to remove the least significant term (highest p-value) and evaluate the new model. Remove one term at a time, and evaluate the new set of estimates and p-values.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I suggest that you use the &lt;A href="https://www.jmp.com/support/help/en/16.2/#page/jmp/introduction-to-profilers.shtml#" target="_self"&gt;Prediction Profiler&lt;/A&gt; once you have select the model to aid in the interpretation of the relationship between the factors and the response.&lt;/P&gt;</description>
      <pubDate>Tue, 03 May 2022 13:05:41 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/interpreting-parameter-estimates/m-p/483861#M72818</guid>
      <dc:creator>Mark_Bailey</dc:creator>
      <dc:date>2022-05-03T13:05:41Z</dc:date>
    </item>
    <item>
      <title>Re: interpreting parameter estimates</title>
      <link>https://community.jmp.com/t5/Discussions/interpreting-parameter-estimates/m-p/483874#M72821</link>
      <description>&lt;P&gt;In addition to Mark's explanation and recommendation, I have the following thoughts:&lt;/P&gt;
&lt;P&gt;1. How much of a change in the response variable is of practical significance? &amp;nbsp;The estimates are indicators of how much the response will change for every "unit" of change in the Parameter.&lt;/P&gt;
&lt;P&gt;2. I don't see the intercept in your parameter estimates table? &amp;nbsp;This is typically the average of the data.&lt;/P&gt;
&lt;P&gt;3. Interactions can be difficult to understand and how to optimize them is dependent on both target value of the response and practical implications. &amp;nbsp;An interaction is when the effect of a factor depends on another factor. &amp;nbsp;For positive sign 2-factor interactions, the effect of the interaction is greater when those factors have the same sign (-,- or +,+), for negative interactions, the effect is greater when they have opposite signs ,(-,+ or +,-). &amp;nbsp;It is good practice to evaluate interactions before drawing conclusions about main effects. &amp;nbsp;Look at the interaction plots for evaluation.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 03 May 2022 13:50:07 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/interpreting-parameter-estimates/m-p/483874#M72821</guid>
      <dc:creator>statman</dc:creator>
      <dc:date>2022-05-03T13:50:07Z</dc:date>
    </item>
    <item>
      <title>Re: interpreting parameter estimates</title>
      <link>https://community.jmp.com/t5/Discussions/interpreting-parameter-estimates/m-p/483913#M72827</link>
      <description>&lt;P&gt;I think that this case is a mixture experiment. so the intercept is present but not explicit.&lt;/P&gt;</description>
      <pubDate>Tue, 03 May 2022 15:54:25 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/interpreting-parameter-estimates/m-p/483913#M72827</guid>
      <dc:creator>Mark_Bailey</dc:creator>
      <dc:date>2022-05-03T15:54:25Z</dc:date>
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