<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Mixed models and r²s in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Mixed-models-and-r-s/m-p/145765#M7614</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi all,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I've been struggling over my data analysis for a while and was hoping you could give me a hand...&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I'm running PROC MIXED because I have non-independent data.&amp;nbsp; I have multiple data points from each of my experimental units, however, due to the nature of my study, I do not have replicates of my treatments.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;My SAS code is as follows: &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc mixed covtest data=AIC IC method=ML;&lt;/P&gt;&lt;P&gt;class stream;&lt;/P&gt;&lt;P&gt;model X = Y / s&amp;nbsp; ddfm=kenwardrogers;&lt;/P&gt;&lt;P&gt;Random intercept /subject=subject;&lt;/P&gt;&lt;P&gt;Run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I have 2 main questions:&amp;nbsp; &lt;/P&gt;&lt;P&gt;1. Since I do not have replication of treatments, is it valid to have the subject in the random statement as there is no way to differentiate between subject and treatment?&amp;nbsp; My understanding of what I have done is not treat subjects a random effect, but rather just told SAS that my X points are not independent, but grouped by subjects and the Kenward-Rogers DDFM will adjust my df accordingly.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;2.&amp;nbsp; Can anyone explain to me in layman's terms how to extract marginal R2s from these models?&amp;nbsp; I have read a number of papers (e.g. Nakagawa 2013, Snijders and Bosker 1994, etc) but I can't seem to grasp exactly how, and the papers giving macros all use 3 models (null, reduced, full), while I can only create null and full models.&amp;nbsp; If you could tell me the parameters to use from the SAS output and provide any citations for your info that would be very much appreciated.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;&lt;P&gt;G.K.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Sun, 16 Mar 2014 22:05:00 GMT</pubDate>
    <dc:creator>gdking</dc:creator>
    <dc:date>2014-03-16T22:05:00Z</dc:date>
    <item>
      <title>Mixed models and r²s</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Mixed-models-and-r-s/m-p/145765#M7614</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi all,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I've been struggling over my data analysis for a while and was hoping you could give me a hand...&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I'm running PROC MIXED because I have non-independent data.&amp;nbsp; I have multiple data points from each of my experimental units, however, due to the nature of my study, I do not have replicates of my treatments.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;My SAS code is as follows: &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc mixed covtest data=AIC IC method=ML;&lt;/P&gt;&lt;P&gt;class stream;&lt;/P&gt;&lt;P&gt;model X = Y / s&amp;nbsp; ddfm=kenwardrogers;&lt;/P&gt;&lt;P&gt;Random intercept /subject=subject;&lt;/P&gt;&lt;P&gt;Run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I have 2 main questions:&amp;nbsp; &lt;/P&gt;&lt;P&gt;1. Since I do not have replication of treatments, is it valid to have the subject in the random statement as there is no way to differentiate between subject and treatment?&amp;nbsp; My understanding of what I have done is not treat subjects a random effect, but rather just told SAS that my X points are not independent, but grouped by subjects and the Kenward-Rogers DDFM will adjust my df accordingly.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;2.&amp;nbsp; Can anyone explain to me in layman's terms how to extract marginal R2s from these models?&amp;nbsp; I have read a number of papers (e.g. Nakagawa 2013, Snijders and Bosker 1994, etc) but I can't seem to grasp exactly how, and the papers giving macros all use 3 models (null, reduced, full), while I can only create null and full models.&amp;nbsp; If you could tell me the parameters to use from the SAS output and provide any citations for your info that would be very much appreciated.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;&lt;P&gt;G.K.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Sun, 16 Mar 2014 22:05:00 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Mixed-models-and-r-s/m-p/145765#M7614</guid>
      <dc:creator>gdking</dc:creator>
      <dc:date>2014-03-16T22:05:00Z</dc:date>
    </item>
    <item>
      <title>Re: Mixed models and r²s</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Mixed-models-and-r-s/m-p/145766#M7615</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Point 1.&amp;nbsp; When you say you have multiple data points from each experimental unit, are these related in either time or space?&amp;nbsp; If so, that might change the approach.&amp;nbsp; However, for now, I would fit the data much as you have, except to change subject=subject to subject=stream.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Point 2. You can form null, reduced and full models.&amp;nbsp; Null would be&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;model x=;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Reduced would be:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;model x=y;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Full would include the random effect as well.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;If that does not give you what I think you are asking for, please post more details about the macros.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Message was edited by: Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 17 Mar 2014 14:43:17 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Mixed-models-and-r-s/m-p/145766#M7615</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2014-03-17T14:43:17Z</dc:date>
    </item>
  </channel>
</rss>

