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    <title>topic Re: CRD w/ subsampling; 5X4X3 factorial how-to? in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/CRD-w-subsampling-5X4X3-factorial-how-to/m-p/22141#M717</link>
    <description>Looks like you have two issues: properly dealing with sub-samples and doing contrasts after model fitting. Here is one approach. You need to have a unique identifier of each replicate of each S, G, and V combination. Call this REP. Let's say there are 5 replicates of each combination of levels of the three fixed effects; there would be five records for S=1,G=1,V=1 (with REP = 1,2,3,4,5), etc. But if you also have sub-samples (let's say 3), then there would be 15 records for S=1,G=1,V=1, etc. There would be three records for S=1,G=1,V=1,REP=1,&lt;BR /&gt;
three records for &lt;BR /&gt;
S=1,G=1,V=1,REP=2,&lt;BR /&gt;
etc. &lt;BR /&gt;
Then you could use the program:&lt;BR /&gt;
proc mixed ;&lt;BR /&gt;
class S G V REP;&lt;BR /&gt;
model Y = S|G|V;&lt;BR /&gt;
random REP(S G V);&lt;BR /&gt;
lsmeans S*G*V / slice = (S G S*G);&lt;BR /&gt;
run;&lt;BR /&gt;
&lt;BR /&gt;
Without the random statement, the procedure would incorrectly consider the sub-samples as independent replicates. &lt;BR /&gt;
&lt;BR /&gt;
You could use a series of contrast statements for the last part of your post. But I can't get into describing this here. Instead, I am showing you how to use the SLICE option on LSMEANS statements. After the means in the output, you will get a series of tests of simple effects. For instance, the first line in the Effect Slice output will be the results of a test for G*V effects for S=1, then for S=2, and so on. Eventually, you will get the test results for V effects for S=1,G=1, then for S=1,G=2, and so on. &lt;BR /&gt;
&lt;BR /&gt;
If you want more specifics, for instance, which varieties are different from each other at S=1,G=1, then for S=1,G=2, and so on, you will need to use GLIMMIX. Everything is the same (in this case) except you can expand the LSMEANS statement to:&lt;BR /&gt;
&lt;BR /&gt;
lsmeans S*G*V / slice = (S G S*G) slicediff=(S G S*G);&lt;BR /&gt;
&lt;BR /&gt;
This will generate a lot of output. You can read about slices in the documentation.</description>
    <pubDate>Sun, 06 Mar 2011 21:09:07 GMT</pubDate>
    <dc:creator>lvm</dc:creator>
    <dc:date>2011-03-06T21:09:07Z</dc:date>
    <item>
      <title>CRD w/ subsampling; 5X4X3 factorial how-to?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/CRD-w-subsampling-5X4X3-factorial-how-to/m-p/22140#M716</link>
      <description>Aloha,&lt;BR /&gt;
&lt;BR /&gt;
I'm trying to analyze my data set but I'm confused on how to program SAS to run what I want it to run.&lt;BR /&gt;
&lt;BR /&gt;
I'm testing the effect of 4 sucrose concentrations and 3 growth promoter concentrations on pollen of 5 plant varieties.  I am using a CRD experimental design, with a complete factorial treatment design.  &lt;BR /&gt;
&lt;BR /&gt;
Is there a way I can test the combinatorial effects of sucrose+growth promoter concentrations on the 5 plant varieties?  For example, I want to test if 5% growth promoter gives significant differences in pollen growth among 5 varieties when that concentration is combined with 4 different levels of sucrose.  Can I do this in a CRD with subsampling?</description>
      <pubDate>Fri, 04 Mar 2011 13:30:48 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/CRD-w-subsampling-5X4X3-factorial-how-to/m-p/22140#M716</guid>
      <dc:creator>KP</dc:creator>
      <dc:date>2011-03-04T13:30:48Z</dc:date>
    </item>
    <item>
      <title>Re: CRD w/ subsampling; 5X4X3 factorial how-to?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/CRD-w-subsampling-5X4X3-factorial-how-to/m-p/22141#M717</link>
      <description>Looks like you have two issues: properly dealing with sub-samples and doing contrasts after model fitting. Here is one approach. You need to have a unique identifier of each replicate of each S, G, and V combination. Call this REP. Let's say there are 5 replicates of each combination of levels of the three fixed effects; there would be five records for S=1,G=1,V=1 (with REP = 1,2,3,4,5), etc. But if you also have sub-samples (let's say 3), then there would be 15 records for S=1,G=1,V=1, etc. There would be three records for S=1,G=1,V=1,REP=1,&lt;BR /&gt;
three records for &lt;BR /&gt;
S=1,G=1,V=1,REP=2,&lt;BR /&gt;
etc. &lt;BR /&gt;
Then you could use the program:&lt;BR /&gt;
proc mixed ;&lt;BR /&gt;
class S G V REP;&lt;BR /&gt;
model Y = S|G|V;&lt;BR /&gt;
random REP(S G V);&lt;BR /&gt;
lsmeans S*G*V / slice = (S G S*G);&lt;BR /&gt;
run;&lt;BR /&gt;
&lt;BR /&gt;
Without the random statement, the procedure would incorrectly consider the sub-samples as independent replicates. &lt;BR /&gt;
&lt;BR /&gt;
You could use a series of contrast statements for the last part of your post. But I can't get into describing this here. Instead, I am showing you how to use the SLICE option on LSMEANS statements. After the means in the output, you will get a series of tests of simple effects. For instance, the first line in the Effect Slice output will be the results of a test for G*V effects for S=1, then for S=2, and so on. Eventually, you will get the test results for V effects for S=1,G=1, then for S=1,G=2, and so on. &lt;BR /&gt;
&lt;BR /&gt;
If you want more specifics, for instance, which varieties are different from each other at S=1,G=1, then for S=1,G=2, and so on, you will need to use GLIMMIX. Everything is the same (in this case) except you can expand the LSMEANS statement to:&lt;BR /&gt;
&lt;BR /&gt;
lsmeans S*G*V / slice = (S G S*G) slicediff=(S G S*G);&lt;BR /&gt;
&lt;BR /&gt;
This will generate a lot of output. You can read about slices in the documentation.</description>
      <pubDate>Sun, 06 Mar 2011 21:09:07 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/CRD-w-subsampling-5X4X3-factorial-how-to/m-p/22141#M717</guid>
      <dc:creator>lvm</dc:creator>
      <dc:date>2011-03-06T21:09:07Z</dc:date>
    </item>
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