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    <title>topic Quintiles and 'proc rank' persistence in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Quintiles-and-proc-rank-persistence/m-p/129036#M6762</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I have data on exam results for 2 years for a number of students. I have a column with the year, the students name and the mark. Some students don't appear in year 2 because they don't sit the second exam. I want to show whether the performance of students persists or whether there's any pattern in their subsequent performance. I can split the data into two halves of equal size to account for the 'first-half' and 'second-half' marks. I can also split the first half into quintiles according to the exam results using 'proc rank'&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I know the output I want is a 5 X 5 table that has the original 5 quintiles on one axis and the 5 subsequent quintiles plus a 'dropped out' category as well, so a 5 x 6 matrix. There will obviously be around 20% of the total number of students in each quintile in the first exam, and if there's no relationship there should be 16.67% in each of the 6 susequent categories. But I don't know how to proceed to show whether this is the case of not with this data. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;How can I go about doing this in SAS, please? Could someone point me towards a good tutorial that would show how to set this up? I've been searching for terms like 'performance persistence' etc, but to no avail. . .&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks in advance.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Fri, 03 May 2013 15:52:44 GMT</pubDate>
    <dc:creator>tobriain</dc:creator>
    <dc:date>2013-05-03T15:52:44Z</dc:date>
    <item>
      <title>Quintiles and 'proc rank' persistence</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Quintiles-and-proc-rank-persistence/m-p/129036#M6762</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I have data on exam results for 2 years for a number of students. I have a column with the year, the students name and the mark. Some students don't appear in year 2 because they don't sit the second exam. I want to show whether the performance of students persists or whether there's any pattern in their subsequent performance. I can split the data into two halves of equal size to account for the 'first-half' and 'second-half' marks. I can also split the first half into quintiles according to the exam results using 'proc rank'&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I know the output I want is a 5 X 5 table that has the original 5 quintiles on one axis and the 5 subsequent quintiles plus a 'dropped out' category as well, so a 5 x 6 matrix. There will obviously be around 20% of the total number of students in each quintile in the first exam, and if there's no relationship there should be 16.67% in each of the 6 susequent categories. But I don't know how to proceed to show whether this is the case of not with this data. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;How can I go about doing this in SAS, please? Could someone point me towards a good tutorial that would show how to set this up? I've been searching for terms like 'performance persistence' etc, but to no avail. . .&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks in advance.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 03 May 2013 15:52:44 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Quintiles-and-proc-rank-persistence/m-p/129036#M6762</guid>
      <dc:creator>tobriain</dc:creator>
      <dc:date>2013-05-03T15:52:44Z</dc:date>
    </item>
    <item>
      <title>Re: Quintiles and 'proc rank' persistence</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Quintiles-and-proc-rank-persistence/m-p/129037#M6763</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;This is how you can get a quintile by quintile table :&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;data test;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;do year= 2011, 2012;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; do student = 1 to 30;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; mark = 40 + floor(60*rand("UNIFORM"));&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; if year=2011 or mod(student,6)&amp;gt;0 then output;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; end;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; end;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;run;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;proc sort data=test; by student year; run;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;proc transpose data=test out=marks prefix=y_;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;by student;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;id year;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;var mark;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;run;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;proc rank data=marks out=quints groups=5;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;var y_:;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;run;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;proc freq data=quints;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;table y_2011*y_2012 / missing;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;run;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;PG&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 03 May 2013 16:17:05 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Quintiles-and-proc-rank-persistence/m-p/129037#M6763</guid>
      <dc:creator>PGStats</dc:creator>
      <dc:date>2013-05-03T16:17:05Z</dc:date>
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