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    <title>topic Which way to do a post hoc test in SAS? in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Which-way-to-do-a-post-hoc-test-in-SAS/m-p/722367#M35000</link>
    <description>&lt;P&gt;Hi all,&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have a dataset (see example below) of the number of social media posts by platform type and account type. I've run a Fisher's exact test which has turned out to be significant and now I want to determine where the actual differences in proportion lie. For example, I'd like to determine if the proportion of posts by Account 1 on Platform1 are significantly different in comparison to all other account types. I've performed a post hoc test where I made a new dichotomous variable, 1=Account 1, 0=all other accounts and then run a Fisher's exact on this 3x2 table.&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;EXAMPLE TABLE:&lt;/STRONG&gt;&lt;/P&gt;&lt;P class="lia-align-left"&gt;Frequency of Posts&lt;/P&gt;&lt;TABLE border="1"&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;Account1&lt;/TD&gt;&lt;TD&gt;Account2&lt;/TD&gt;&lt;TD&gt;Account3&lt;/TD&gt;&lt;TD&gt;Account4&lt;/TD&gt;&lt;TD&gt;Account5&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform1&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform2&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform3&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&lt;STRONG&gt;QUESTIONS:&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;1)&lt;/STRONG&gt; I'm wondering if based on my aims, it's correct to group the columns as I have for a post hoc test. Most examples of pairwise comparisons as post hoc tests that I've seen tend to group the rows rather than the columns.&amp;nbsp;&lt;/P&gt;&lt;P&gt;EXAMPLE PAIRWISE COMPARISON&lt;/P&gt;&lt;TABLE border="1"&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;Account1&lt;/TD&gt;&lt;TD&gt;All other accounts&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform1&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform2&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform3&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&lt;STRONG&gt;Bonferroni p&amp;lt;0.0001&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;2)&lt;/STRONG&gt; From my output, I get 5 p values (1 per each account type). For example, if the p value of my first pairwise comparison (see example above) is significant, then does this mean that there is a significant difference in the proportion of posts for Account1 compared to all other accounts for each of the 3 platforms? Is there a way in SAS to determine which exact cells within one row are significantly different between account types?&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;/P&gt;</description>
    <pubDate>Sat, 27 Feb 2021 22:32:38 GMT</pubDate>
    <dc:creator>monsterpie</dc:creator>
    <dc:date>2021-02-27T22:32:38Z</dc:date>
    <item>
      <title>Which way to do a post hoc test in SAS?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Which-way-to-do-a-post-hoc-test-in-SAS/m-p/722367#M35000</link>
      <description>&lt;P&gt;Hi all,&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have a dataset (see example below) of the number of social media posts by platform type and account type. I've run a Fisher's exact test which has turned out to be significant and now I want to determine where the actual differences in proportion lie. For example, I'd like to determine if the proportion of posts by Account 1 on Platform1 are significantly different in comparison to all other account types. I've performed a post hoc test where I made a new dichotomous variable, 1=Account 1, 0=all other accounts and then run a Fisher's exact on this 3x2 table.&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;EXAMPLE TABLE:&lt;/STRONG&gt;&lt;/P&gt;&lt;P class="lia-align-left"&gt;Frequency of Posts&lt;/P&gt;&lt;TABLE border="1"&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;Account1&lt;/TD&gt;&lt;TD&gt;Account2&lt;/TD&gt;&lt;TD&gt;Account3&lt;/TD&gt;&lt;TD&gt;Account4&lt;/TD&gt;&lt;TD&gt;Account5&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform1&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform2&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform3&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&lt;STRONG&gt;QUESTIONS:&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;1)&lt;/STRONG&gt; I'm wondering if based on my aims, it's correct to group the columns as I have for a post hoc test. Most examples of pairwise comparisons as post hoc tests that I've seen tend to group the rows rather than the columns.&amp;nbsp;&lt;/P&gt;&lt;P&gt;EXAMPLE PAIRWISE COMPARISON&lt;/P&gt;&lt;TABLE border="1"&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;Account1&lt;/TD&gt;&lt;TD&gt;All other accounts&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform1&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform2&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;Platform3&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&lt;STRONG&gt;Bonferroni p&amp;lt;0.0001&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;2)&lt;/STRONG&gt; From my output, I get 5 p values (1 per each account type). For example, if the p value of my first pairwise comparison (see example above) is significant, then does this mean that there is a significant difference in the proportion of posts for Account1 compared to all other accounts for each of the 3 platforms? Is there a way in SAS to determine which exact cells within one row are significantly different between account types?&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;/P&gt;</description>
      <pubDate>Sat, 27 Feb 2021 22:32:38 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Which-way-to-do-a-post-hoc-test-in-SAS/m-p/722367#M35000</guid>
      <dc:creator>monsterpie</dc:creator>
      <dc:date>2021-02-27T22:32:38Z</dc:date>
    </item>
    <item>
      <title>Re: Which way to do a post hoc test in SAS?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Which-way-to-do-a-post-hoc-test-in-SAS/m-p/722479#M35008</link>
      <description>&lt;P&gt;See &lt;A href="http://support.sas.com/kb/22/565.html" target="_self"&gt;this note&lt;/A&gt;. You might want to fit a Poisson model and then use LSMESTIMATE statements as shown in the log linear model section there to make the comparisons. If desired, you could then gather all of the p-values in a data set and then use PROC MULTTEST to do an adjustment for multiple testing as shown earlier in the note.&lt;/P&gt;</description>
      <pubDate>Sun, 28 Feb 2021 20:32:53 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Which-way-to-do-a-post-hoc-test-in-SAS/m-p/722479#M35008</guid>
      <dc:creator>StatDave</dc:creator>
      <dc:date>2021-02-28T20:32:53Z</dc:date>
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