<?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 Re: Flag overlapping 95% CLs in SAS Programming</title>
    <link>https://communities.sas.com/t5/SAS-Programming/Flag-overlapping-95-CLs/m-p/823863#M325345</link>
    <description>&lt;P&gt;Please show us the code that created these confidence intervals.&lt;/P&gt;</description>
    <pubDate>Mon, 18 Jul 2022 15:10:57 GMT</pubDate>
    <dc:creator>PaigeMiller</dc:creator>
    <dc:date>2022-07-18T15:10:57Z</dc:date>
    <item>
      <title>Flag overlapping 95% CLs</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Flag-overlapping-95-CLs/m-p/823861#M325344</link>
      <description>&lt;P&gt;I want to find a way to flag or otherwise ID the ranges of 95% CLs for a series of datasets I have.&amp;nbsp;&lt;/P&gt;
&lt;DIV class="branch"&gt;
&lt;DIV&gt;
&lt;DIV align="center"&gt;
&lt;TABLE class="table" summary="Procedure Print: Data Set WORK.CROSS_VIT_UNPD_SKP_C" frame="box" rules="all" cellspacing="0" cellpadding="5"&gt;
&lt;THEAD&gt;
&lt;TR&gt;
&lt;TH class="r header" scope="col" width="24.5781px" height="19px"&gt;Obs&lt;/TH&gt;
&lt;TH class="r header" scope="col" width="40px" height="19px"&gt;FPL&lt;/TH&gt;
&lt;TH class="r header" scope="col" width="75.3906px" height="19px"&gt;RowPercent&lt;/TH&gt;
&lt;TH class="r header" scope="col" width="81.0156px" height="19px"&gt;RowLowerCL&lt;/TH&gt;
&lt;TH class="r header" scope="col" width="80px" height="19px"&gt;RowUpperCL&lt;/TH&gt;
&lt;/TR&gt;
&lt;/THEAD&gt;
&lt;TBODY&gt;
&lt;TR&gt;
&lt;TH class="r rowheader" scope="row" width="24.5781px" height="30px"&gt;1&lt;/TH&gt;
&lt;TD width="40px" height="30px" class="r data"&gt;1&lt;/TD&gt;
&lt;TD width="75.3906px" height="30px" class="r data"&gt;67.4&lt;/TD&gt;
&lt;TD width="81.0156px" height="30px" class="r data"&gt;63.5&lt;/TD&gt;
&lt;TD width="80px" height="30px" class="r data"&gt;71.4&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="r rowheader" scope="row" width="24.5781px" height="30px"&gt;2&lt;/TH&gt;
&lt;TD width="40px" height="30px" class="r data"&gt;2&lt;/TD&gt;
&lt;TD width="75.3906px" height="30px" class="r data"&gt;68.0&lt;/TD&gt;
&lt;TD width="81.0156px" height="30px" class="r data"&gt;62.5&lt;/TD&gt;
&lt;TD width="80px" height="30px" class="r data"&gt;73.6&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="r rowheader" scope="row" width="24.5781px" height="30px"&gt;3&lt;/TH&gt;
&lt;TD width="40px" height="30px" class="r data"&gt;3&lt;/TD&gt;
&lt;TD width="75.3906px" height="30px" class="r data"&gt;63.8&lt;/TD&gt;
&lt;TD width="81.0156px" height="30px" class="r data"&gt;56.2&lt;/TD&gt;
&lt;TD width="80px" height="30px" class="r data"&gt;71.4&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="r rowheader" scope="row" width="24.5781px" height="39px"&gt;4&lt;/TH&gt;
&lt;TD width="40px" height="39px" class="r data"&gt;4&lt;/TD&gt;
&lt;TD width="75.3906px" height="39px" class="r data"&gt;51.1&lt;/TD&gt;
&lt;TD width="81.0156px" height="39px" class="r data"&gt;42.0&lt;/TD&gt;
&lt;TD width="80px" height="39px" class="r data"&gt;60.3&lt;/TD&gt;
&lt;/TR&gt;
&lt;/TBODY&gt;
&lt;/TABLE&gt;
&lt;P class="lia-align-left"&gt;These datasets are outputs from previous crosstabulations. I run Chi-square tests for these crosstabulations as well, but I want a visual way to ID and get a sense of which CLs overlap with all the others (not just compare FPL=1-2, 2-3, etc.).&lt;/P&gt;
&lt;P class="lia-align-left"&gt;&amp;nbsp;&lt;/P&gt;
&lt;P class="lia-align-left"&gt;I've come across various approaches to ID consecutive data ranges that overlap, largely with first./last. and retain statements, but they don't work for my situation. I think a matrix might be best to concisely ID the unique pairs, but I'm not sure how to approach that.&amp;nbsp;&lt;/P&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;</description>
      <pubDate>Mon, 18 Jul 2022 15:05:35 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Flag-overlapping-95-CLs/m-p/823861#M325344</guid>
      <dc:creator>SAS93</dc:creator>
      <dc:date>2022-07-18T15:05:35Z</dc:date>
    </item>
    <item>
      <title>Re: Flag overlapping 95% CLs</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Flag-overlapping-95-CLs/m-p/823863#M325345</link>
      <description>&lt;P&gt;Please show us the code that created these confidence intervals.&lt;/P&gt;</description>
      <pubDate>Mon, 18 Jul 2022 15:10:57 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Flag-overlapping-95-CLs/m-p/823863#M325345</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2022-07-18T15:10:57Z</dc:date>
    </item>
    <item>
      <title>Re: Flag overlapping 95% CLs</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Flag-overlapping-95-CLs/m-p/823867#M325346</link>
      <description>&lt;P&gt;Something like this perhaps:&lt;/P&gt;
&lt;PRE&gt;data have;
   input FPL 	RowPercent 	RowLowerCL 	RowUpperCL;
datalines;
1 	67.4 	63.5 	71.4
2 	68.0 	62.5 	73.6
3 	63.8 	56.2 	71.4
4 	51.1 	42.0 	60.3
;

proc sgplot data=have;
   highlow x=fpl  low=rowlowercl high=rowuppercl;
   xaxis type=discrete;
run;&lt;/PRE&gt;
&lt;P&gt;Note the use of data step code to provide example data. That way we can write code to use your example data.&lt;/P&gt;</description>
      <pubDate>Mon, 18 Jul 2022 15:16:14 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Flag-overlapping-95-CLs/m-p/823867#M325346</guid>
      <dc:creator>ballardw</dc:creator>
      <dc:date>2022-07-18T15:16:14Z</dc:date>
    </item>
    <item>
      <title>Re: Flag overlapping 95% CLs</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Flag-overlapping-95-CLs/m-p/823911#M325360</link>
      <description>&lt;P&gt;If you are trying to see whether the means of different categories are significant;y different from each other, be sure to correct for multiple comparisons.&amp;nbsp;Please see the visualizations that are created automatically by using PROC GLM, such as&amp;nbsp;&lt;/P&gt;
&lt;UL&gt;
&lt;LI&gt;&lt;A href="https://blogs.sas.com/content/iml/2017/10/16/multiple-comparisons-lines-plot.html" target="_self"&gt;Graphs for multiple comparisons of means: The lines plot&lt;/A&gt;&lt;/LI&gt;
&lt;LI&gt;&lt;A href="https://blogs.sas.com/content/iml/2017/10/18/diffogram-multiple-comparisons-sas.html" target="_self"&gt;The diffogram and other graphs for multiple comparisons of means&lt;/A&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;Be aware that the overlapping of 95% CIs is neither necessary nor sufficient for inferring that the difference between the means is significant.&lt;/P&gt;</description>
      <pubDate>Mon, 18 Jul 2022 17:47:21 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Flag-overlapping-95-CLs/m-p/823911#M325360</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2022-07-18T17:47:21Z</dc:date>
    </item>
  </channel>
</rss>

