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    <title>topic Re: Testing for an effect of a treatment on an ordinal score beyond Kruskall-Wallis... in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Testing-for-an-effect-of-a-treatment-on-an-ordinal-score-beyond/m-p/530528#M26771</link>
    <description>&lt;P&gt;You can try an ordinal regression.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The documentation has a fully worked example:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://documentation.sas.com/?docsetId=statug&amp;amp;docsetTarget=statug_logistic_examples03.htm&amp;amp;docsetVersion=15.1&amp;amp;locale=en" target="_blank"&gt;https://documentation.sas.com/?docsetId=statug&amp;amp;docsetTarget=statug_logistic_examples03.htm&amp;amp;docsetVersion=15.1&amp;amp;locale=en&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Under the title there's a link to the full code that you can run on your machine and then follow through. Once you understand the example, you can replicate it on your own data.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/118159"&gt;@SBuc&lt;/a&gt;&amp;nbsp;wrote:&lt;BR /&gt;
&lt;P&gt;Dear Brain trust,&lt;/P&gt;
&lt;P&gt;I want to determine the effect of a treatment on a score of pain in animals. Many published literature has used GLM models using score as a continuous dependent variable accounting then for treatment, block and animal repetition using linear mixed model.&lt;/P&gt;
&lt;P&gt;however, this approach is per se assuming that the score is a continuous variable (which is not) and also that a score of 8 is 2 times worst than a score of 4 which is not demonstrated (so the interval between 2 unit scale can not be assumed to be the same throughout the scale (0-15 max points).&lt;/P&gt;
&lt;P&gt;initially we used non parametric tests such as rank comparison but I want to know if a more elegant and powerful analysis can be performed.&lt;/P&gt;
&lt;P&gt;thanks&lt;/P&gt;
&lt;HR /&gt;&lt;/BLOCKQUOTE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Mon, 28 Jan 2019 02:02:47 GMT</pubDate>
    <dc:creator>Reeza</dc:creator>
    <dc:date>2019-01-28T02:02:47Z</dc:date>
    <item>
      <title>Testing for an effect of a treatment on an ordinal score beyond Kruskall-Wallis...</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Testing-for-an-effect-of-a-treatment-on-an-ordinal-score-beyond/m-p/530452#M26765</link>
      <description>&lt;P&gt;Dear Brain trust,&lt;/P&gt;&lt;P&gt;I want to determine the effect of a treatment on a score of pain in animals. Many published literature has used GLM models using score as a continuous dependent variable accounting then for treatment, block and animal repetition using linear mixed model.&lt;/P&gt;&lt;P&gt;however, this approach is per se assuming that the score is a continuous variable (which is not) and also that a score of 8 is 2 times worst than a score of 4 which is not demonstrated (so the interval between 2 unit scale can not be assumed to be the same throughout the scale (0-15 max points).&lt;/P&gt;&lt;P&gt;initially we used non parametric tests such as rank comparison but I want to know if a more elegant and powerful analysis can be performed.&lt;/P&gt;&lt;P&gt;thanks&lt;/P&gt;</description>
      <pubDate>Sun, 27 Jan 2019 12:11:14 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Testing-for-an-effect-of-a-treatment-on-an-ordinal-score-beyond/m-p/530452#M26765</guid>
      <dc:creator>SBuc</dc:creator>
      <dc:date>2019-01-27T12:11:14Z</dc:date>
    </item>
    <item>
      <title>Re: Testing for an effect of a treatment on an ordinal score beyond Kruskall-Wallis...</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Testing-for-an-effect-of-a-treatment-on-an-ordinal-score-beyond/m-p/530528#M26771</link>
      <description>&lt;P&gt;You can try an ordinal regression.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The documentation has a fully worked example:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://documentation.sas.com/?docsetId=statug&amp;amp;docsetTarget=statug_logistic_examples03.htm&amp;amp;docsetVersion=15.1&amp;amp;locale=en" target="_blank"&gt;https://documentation.sas.com/?docsetId=statug&amp;amp;docsetTarget=statug_logistic_examples03.htm&amp;amp;docsetVersion=15.1&amp;amp;locale=en&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Under the title there's a link to the full code that you can run on your machine and then follow through. Once you understand the example, you can replicate it on your own data.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/118159"&gt;@SBuc&lt;/a&gt;&amp;nbsp;wrote:&lt;BR /&gt;
&lt;P&gt;Dear Brain trust,&lt;/P&gt;
&lt;P&gt;I want to determine the effect of a treatment on a score of pain in animals. Many published literature has used GLM models using score as a continuous dependent variable accounting then for treatment, block and animal repetition using linear mixed model.&lt;/P&gt;
&lt;P&gt;however, this approach is per se assuming that the score is a continuous variable (which is not) and also that a score of 8 is 2 times worst than a score of 4 which is not demonstrated (so the interval between 2 unit scale can not be assumed to be the same throughout the scale (0-15 max points).&lt;/P&gt;
&lt;P&gt;initially we used non parametric tests such as rank comparison but I want to know if a more elegant and powerful analysis can be performed.&lt;/P&gt;
&lt;P&gt;thanks&lt;/P&gt;
&lt;HR /&gt;&lt;/BLOCKQUOTE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 28 Jan 2019 02:02:47 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Testing-for-an-effect-of-a-treatment-on-an-ordinal-score-beyond/m-p/530528#M26771</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2019-01-28T02:02:47Z</dc:date>
    </item>
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