<?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 Permutational MANOVA in SAS? in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Permutational-MANOVA-in-SAS/m-p/166045#M8686</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I have the following design:&lt;/P&gt;&lt;P&gt;60 Plants assigned to treatment A (with, without)&lt;/P&gt;&lt;P&gt;Variables V1 and V2 have been measured at the plant level (e.g. biomass)&lt;/P&gt;&lt;P&gt;We selected three leaves per plant (young, intermediate, old) and measured three variables per leaf (V3, V4, V5). Thus, we have a kind of split-plot design.&lt;/P&gt;&lt;P&gt;We now want to know how treatment A affects "plant phenotype" which is characterized by variables V1, V2 (plant level) and V3-V5 (leaf level). Of course, we can use a linear model for each variable separately, but we need to have a measure how the plant "as a whole" was affected by A.&lt;/P&gt;&lt;P&gt;We think that analyzing dissimilarity matrices from all plant traits might be a good option to assess the effect of A. In R, there is a package available (adonis) which does a "permutational MANOVA". I wonder if there is something similar possible in SAS.&lt;/P&gt;&lt;P&gt;Further, I am not sure how to deal with the split-plot structure of leaf data in such permutation tests.&lt;/P&gt;&lt;P&gt;Many thanx for every idea!!!!&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Tue, 20 May 2014 12:59:46 GMT</pubDate>
    <dc:creator>Tetrix</dc:creator>
    <dc:date>2014-05-20T12:59:46Z</dc:date>
    <item>
      <title>Permutational MANOVA in SAS?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Permutational-MANOVA-in-SAS/m-p/166045#M8686</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I have the following design:&lt;/P&gt;&lt;P&gt;60 Plants assigned to treatment A (with, without)&lt;/P&gt;&lt;P&gt;Variables V1 and V2 have been measured at the plant level (e.g. biomass)&lt;/P&gt;&lt;P&gt;We selected three leaves per plant (young, intermediate, old) and measured three variables per leaf (V3, V4, V5). Thus, we have a kind of split-plot design.&lt;/P&gt;&lt;P&gt;We now want to know how treatment A affects "plant phenotype" which is characterized by variables V1, V2 (plant level) and V3-V5 (leaf level). Of course, we can use a linear model for each variable separately, but we need to have a measure how the plant "as a whole" was affected by A.&lt;/P&gt;&lt;P&gt;We think that analyzing dissimilarity matrices from all plant traits might be a good option to assess the effect of A. In R, there is a package available (adonis) which does a "permutational MANOVA". I wonder if there is something similar possible in SAS.&lt;/P&gt;&lt;P&gt;Further, I am not sure how to deal with the split-plot structure of leaf data in such permutation tests.&lt;/P&gt;&lt;P&gt;Many thanx for every idea!!!!&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 20 May 2014 12:59:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Permutational-MANOVA-in-SAS/m-p/166045#M8686</guid>
      <dc:creator>Tetrix</dc:creator>
      <dc:date>2014-05-20T12:59:46Z</dc:date>
    </item>
    <item>
      <title>Re: Permutational MANOVA in SAS?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Permutational-MANOVA-in-SAS/m-p/166046#M8687</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Search the SUGI 27 proceedings for a paper by David Cassell--A Randomization-test Wrapper for SAS PROCs.&amp;nbsp; There is a macro %RAND__GEN that may be able to do what you need.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 20 May 2014 15:00:47 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Permutational-MANOVA-in-SAS/m-p/166046#M8687</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2014-05-20T15:00:47Z</dc:date>
    </item>
    <item>
      <title>Re: Permutational MANOVA in SAS?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Permutational-MANOVA-in-SAS/m-p/166047#M8688</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thank you, this is very interesting and probably a first step! However, I am not sure how to deal with the fact that some variables have been measured on the whole plant-level whilst other variables have been measured on subplots (leaves of differing age) within he plant. Thus, combining both types of variable seems to be a bit of a problem...&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 22 May 2014 05:29:02 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Permutational-MANOVA-in-SAS/m-p/166047#M8688</guid>
      <dc:creator>Tetrix</dc:creator>
      <dc:date>2014-05-22T05:29:02Z</dc:date>
    </item>
    <item>
      <title>Re: Permutational MANOVA in SAS?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Permutational-MANOVA-in-SAS/m-p/166048#M8689</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Mmm, that does pose some problems.&amp;nbsp; I haven't tried it recently, but I think the wrapper does handle (or can be set up to handle) hierarchical structures.&amp;nbsp; If not, contacting the author might be in order.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 22 May 2014 12:47:45 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Permutational-MANOVA-in-SAS/m-p/166048#M8689</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2014-05-22T12:47:45Z</dc:date>
    </item>
  </channel>
</rss>

