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    <title>topic Re: Ordinal logistic regression in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Ordinal-logistic-regression/m-p/407279#M65730</link>
    <description>&lt;P&gt;You might use the difference between the 'cumulative logits' behind the ordinal logistic regression model and the 'generalized logits' behind the nominal logistic regression model. The ordinal logistic model is more restrictive, so the same coefficients apply. The only difference between levels is the intercept value. On the other hand, the nominal logistic model uses a full set of parameters for each level.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You might compare the results of the ordinal logistic regression to the results of the nominal logistic regression to determine if the restriction is valid.&lt;/P&gt;</description>
    <pubDate>Thu, 05 Aug 2021 14:20:31 GMT</pubDate>
    <dc:creator>Mark_Bailey</dc:creator>
    <dc:date>2021-08-05T14:20:31Z</dc:date>
    <item>
      <title>Ordinal logistic regression</title>
      <link>https://community.jmp.com/t5/Discussions/Ordinal-logistic-regression/m-p/407255#M65726</link>
      <description>&lt;P&gt;&lt;FONT size="2"&gt;I am using JMP (Fit Model) to do a ordinal logistic regression.&lt;/FONT&gt;&lt;/P&gt;&lt;P&gt;&lt;FONT size="2"&gt;Now I am looking for a way to do a test the assumption that "proportional odds" are involved in my model.&lt;/FONT&gt;&lt;/P&gt;&lt;P&gt;&lt;FONT size="2"&gt;Does anyone know how to do this? Or is there a possibiltity that JMP does this kind of test (also referred to as "&lt;SPAN style="font-size: 10.0pt; font-family: 'Verdana',sans-serif;"&gt;Approximate likelihood-ratio test of proportionality of odds" or "&lt;/SPAN&gt;&lt;SPAN style="font-size: 10.0pt; font-family: 'Verdana',sans-serif;"&gt;Brant Test of Parallel Regression &lt;FONT color="#333333"&gt;Assumption"&lt;/FONT&gt; or &lt;FONT color="#333300"&gt;"score Test for the proportional odds assumption" automatically before running the model? &lt;/FONT&gt;&lt;/SPAN&gt;&lt;/FONT&gt;&lt;/P&gt;&lt;P&gt;&lt;FONT size="2"&gt;&lt;SPAN style="font-size: 10.0pt; font-family: 'Verdana',sans-serif;"&gt;&lt;FONT color="#333300"&gt;Any help would be much appreciated!&amp;nbsp; &lt;/FONT&gt;&lt;/SPAN&gt;&lt;/FONT&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 09 Jun 2023 00:37:09 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Ordinal-logistic-regression/m-p/407255#M65726</guid>
      <dc:creator>Ina123</dc:creator>
      <dc:date>2023-06-09T00:37:09Z</dc:date>
    </item>
    <item>
      <title>Re: Ordinal logistic regression</title>
      <link>https://community.jmp.com/t5/Discussions/Ordinal-logistic-regression/m-p/407279#M65730</link>
      <description>&lt;P&gt;You might use the difference between the 'cumulative logits' behind the ordinal logistic regression model and the 'generalized logits' behind the nominal logistic regression model. The ordinal logistic model is more restrictive, so the same coefficients apply. The only difference between levels is the intercept value. On the other hand, the nominal logistic model uses a full set of parameters for each level.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You might compare the results of the ordinal logistic regression to the results of the nominal logistic regression to determine if the restriction is valid.&lt;/P&gt;</description>
      <pubDate>Thu, 05 Aug 2021 14:20:31 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Ordinal-logistic-regression/m-p/407279#M65730</guid>
      <dc:creator>Mark_Bailey</dc:creator>
      <dc:date>2021-08-05T14:20:31Z</dc:date>
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