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    <title>topic Re: Looking for SAS code of &amp;quot;joint random effect model&amp;quot; for two ordinal responses in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672734#M32194</link>
    <description>&lt;P&gt;Many results when looking for:&amp;nbsp;&amp;nbsp;&lt;STRONG&gt;sas "joint random effect model"&amp;nbsp; &amp;nbsp;&lt;/STRONG&gt;on the web.&lt;/P&gt;
&lt;P&gt;What have you tried? Have you looked at proc mixed?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Tue, 28 Jul 2020 05:09:14 GMT</pubDate>
    <dc:creator>ChrisNZ</dc:creator>
    <dc:date>2020-07-28T05:09:14Z</dc:date>
    <item>
      <title>Looking for SAS code of "joint random effect model" for two ordinal responses</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672703#M32193</link>
      <description>&lt;P&gt;Dear all,&lt;/P&gt;
&lt;P&gt;I'm now handling with longitudinal data analysis.&lt;/P&gt;
&lt;P&gt;I am Looking for the code of "joint random effect model" for two ordinal responses.&lt;/P&gt;
&lt;P&gt;I also&amp;nbsp;Looking for the code of "joint marginalized model"&amp;nbsp;for two ordinal responses.&lt;/P&gt;
&lt;P&gt;does anyone have an example code?&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;Is there anybody having experience with this statistical methods and SAS program for this analysis?&lt;/SPAN&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 27 Jul 2020 22:59:06 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672703#M32193</guid>
      <dc:creator>MahdiA110</dc:creator>
      <dc:date>2020-07-27T22:59:06Z</dc:date>
    </item>
    <item>
      <title>Re: Looking for SAS code of "joint random effect model" for two ordinal responses</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672734#M32194</link>
      <description>&lt;P&gt;Many results when looking for:&amp;nbsp;&amp;nbsp;&lt;STRONG&gt;sas "joint random effect model"&amp;nbsp; &amp;nbsp;&lt;/STRONG&gt;on the web.&lt;/P&gt;
&lt;P&gt;What have you tried? Have you looked at proc mixed?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 28 Jul 2020 05:09:14 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672734#M32194</guid>
      <dc:creator>ChrisNZ</dc:creator>
      <dc:date>2020-07-28T05:09:14Z</dc:date>
    </item>
    <item>
      <title>Re: Looking for SAS code of "joint random effect model" for two ordinal responses</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672738#M32195</link>
      <description>&lt;P&gt;Yes I did.&lt;/P&gt;
&lt;P&gt;But I could not find any practical example for &lt;FONT size="5"&gt;&lt;U&gt;jointing &lt;/U&gt;&lt;/FONT&gt;two ordinal responses in &lt;SPAN&gt;longitudinal data&lt;/SPAN&gt;.&lt;/P&gt;
&lt;P&gt;I do NOT know how to joint these responses!&lt;/P&gt;
&lt;P&gt;Do you have the link of example?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 28 Jul 2020 05:59:42 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672738#M32195</guid>
      <dc:creator>MahdiA110</dc:creator>
      <dc:date>2020-07-28T05:59:42Z</dc:date>
    </item>
    <item>
      <title>Re: Looking for SAS code of "joint random effect model" for two ordinal responses</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672766#M32196</link>
      <description>&lt;P&gt;Moved to &lt;EM&gt;stats&lt;/EM&gt; community where you have more chances of getting help.&lt;/P&gt;</description>
      <pubDate>Tue, 28 Jul 2020 11:19:59 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672766#M32196</guid>
      <dc:creator>ChrisNZ</dc:creator>
      <dc:date>2020-07-28T11:19:59Z</dc:date>
    </item>
    <item>
      <title>Re: Looking for SAS code of "joint random effect model" for two ordinal responses</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672796#M32201</link>
      <description>&lt;P&gt;I almost started giving an answer without asking some questions first.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;1. When you say a joint ordinal response, my first thought is that you have some sort of panel data (2 endpoints per subject) measured repeatedly.&amp;nbsp; That really doesn't fit the schema for any of the SAS/STAT procedures, but possibly PROC PANEL in the SAS/ETS suite could handle this.&amp;nbsp; That is only a possibility.&lt;/P&gt;
&lt;P&gt;2. What are the two ordinal variables?&amp;nbsp; Is there enough levels in either to possibly consider the response as continuous?&amp;nbsp; If that is the case, then PROC GLIMMIX offers some hope for fitting variables with different distributions.&amp;nbsp; However, multinomial distributions are a pain, and I don't know if you can use the approach in the example where a joint model is fit to binary and count data.&lt;/P&gt;
&lt;P&gt;3. What do you mean by "joint random effect"?&amp;nbsp; Random effects are not response variables, which is what comes to my mind when I think of "joint" analysis.&amp;nbsp; Are you talking random intercept type models?&amp;nbsp; Clarification of this will really help.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;SteveDenham&lt;/P&gt;</description>
      <pubDate>Tue, 28 Jul 2020 12:25:01 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672796#M32201</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2020-07-28T12:25:01Z</dc:date>
    </item>
    <item>
      <title>Re: Looking for SAS code of "joint random effect model" for two ordinal responses</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672845#M32206</link>
      <description>&lt;P&gt;Dear Dr SteveDenham;&lt;/P&gt;
&lt;P&gt;This is my thesis. I have two ordinal variable which categorized in three levels. These are my responses which shows the severity of disease in my research. I want to build three models and compare them to find the best one. I meant, i need to assessed the joint effect of two measures simultaneously and see the results.&lt;/P&gt;
&lt;P&gt;Now the problem is that i can not find appropriate code for jointing my two responses.&lt;/P&gt;
&lt;P&gt;I assessed some studied which had the same goal. But there is only the result and codes are not available in articles!&lt;/P&gt;
&lt;P&gt;Do you know any similar example for it?&lt;/P&gt;</description>
      <pubDate>Tue, 28 Jul 2020 14:18:40 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672845#M32206</guid>
      <dc:creator>MahdiA110</dc:creator>
      <dc:date>2020-07-28T14:18:40Z</dc:date>
    </item>
    <item>
      <title>Re: Looking for SAS code of "joint random effect model" for two ordinal responses</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672857#M32207</link>
      <description>&lt;P&gt;Not a bit of experience, so I am just going to throw an idea at you.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Use PROC PRINCOMP to get the first principal component and the "joint score" for each individual.&amp;nbsp; The information about the principal component will tell you how much of the total variability is explained by that component - in other words, how 'jointly' the two measures are related.&amp;nbsp;Once you have this "joint score", you can then proceed to whatever analysis you might choose.&amp;nbsp; This example shows how this was done for a 1 to 10 scale for 14 variables:&amp;nbsp;&lt;A href="https://documentation.sas.com/?docsetId=statug&amp;amp;docsetTarget=statug_princomp_examples03.htm&amp;amp;docsetVersion=14.3&amp;amp;locale=en" target="_self"&gt;https://documentation.sas.com/?docsetId=statug&amp;amp;docsetTarget=statug_princomp_examples03.htm&amp;amp;docsetVersion=14.3&amp;amp;locale=en&lt;/A&gt;&amp;nbsp;.&amp;nbsp; In your case you have a 1 to 3 scale for 2 variables.&amp;nbsp; To truly separate things, you will likely need a lot of data, but at least that example should get you started.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;SteveDenham&lt;/P&gt;</description>
      <pubDate>Tue, 28 Jul 2020 14:37:47 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/672857#M32207</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2020-07-28T14:37:47Z</dc:date>
    </item>
    <item>
      <title>Re: Looking for SAS code of "joint random effect model" for two ordinal responses</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/673843#M32245</link>
      <description>Thank you so much Dr Denhman</description>
      <pubDate>Fri, 31 Jul 2020 22:13:33 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Looking-for-SAS-code-of-quot-joint-random-effect-model-quot-for/m-p/673843#M32245</guid>
      <dc:creator>MahdiA110</dc:creator>
      <dc:date>2020-07-31T22:13:33Z</dc:date>
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