<?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: Log +1 transformations and geometric means in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Log-1-transformations-and-geometric-means/m-p/342906#M18040</link>
    <description>&lt;P&gt;I don't think you want the geometric mean of the log-transformed values. You want the arithmetic mean.&lt;/P&gt;
&lt;P&gt;The reason is that the geometric mean of the original data is equal to the logarithm of the geometric mean of the transformed data.&lt;/P&gt;
&lt;P&gt;In symbols, if y_i = log(x_i), then&lt;/P&gt;
&lt;P&gt;mean(y) =&lt;SPAN&gt; (1/n) Sum y_i =&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN&gt; (1/n) Sum log(x_i) = log( (Prod x_i)^(1/n) = log( GeoMean(x) )&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;or&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;exp( mean(y) ) = GeoMean(x)&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;When you add 1 to the data, you are changing the reference value for the measurement. There is not always an easy way to interpret statistics on&amp;nbsp;the log(x+1) scale in terms of the original measurements. This fact does not invalidate the transformation, it just means that the results are harder to interpret.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Tue, 21 Mar 2017 11:58:47 GMT</pubDate>
    <dc:creator>Rick_SAS</dc:creator>
    <dc:date>2017-03-21T11:58:47Z</dc:date>
    <item>
      <title>Log +1 transformations and geometric means</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Log-1-transformations-and-geometric-means/m-p/342853#M18038</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have a dataset that requires a log transformation due to skewed data. However, performing a log transformation changes some of my values to negative values, which do not allow me to obtain a geometric mean. Those values are still of importance to my analysis, so I was adviced to use a log +1 transformation.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;My question is will using the command PROC SURVEYMEANS with ALLGEO to calculate the geometric mean take into account the "+1" in the log +1 transformation or does that have to be factored in the sas code.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Any advice is greatly appreciated.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Mark&lt;/P&gt;</description>
      <pubDate>Tue, 21 Mar 2017 06:41:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Log-1-transformations-and-geometric-means/m-p/342853#M18038</guid>
      <dc:creator>MVP</dc:creator>
      <dc:date>2017-03-21T06:41:22Z</dc:date>
    </item>
    <item>
      <title>Re: Log +1 transformations and geometric means</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Log-1-transformations-and-geometric-means/m-p/342906#M18040</link>
      <description>&lt;P&gt;I don't think you want the geometric mean of the log-transformed values. You want the arithmetic mean.&lt;/P&gt;
&lt;P&gt;The reason is that the geometric mean of the original data is equal to the logarithm of the geometric mean of the transformed data.&lt;/P&gt;
&lt;P&gt;In symbols, if y_i = log(x_i), then&lt;/P&gt;
&lt;P&gt;mean(y) =&lt;SPAN&gt; (1/n) Sum y_i =&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN&gt; (1/n) Sum log(x_i) = log( (Prod x_i)^(1/n) = log( GeoMean(x) )&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;or&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;exp( mean(y) ) = GeoMean(x)&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;When you add 1 to the data, you are changing the reference value for the measurement. There is not always an easy way to interpret statistics on&amp;nbsp;the log(x+1) scale in terms of the original measurements. This fact does not invalidate the transformation, it just means that the results are harder to interpret.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 21 Mar 2017 11:58:47 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Log-1-transformations-and-geometric-means/m-p/342906#M18040</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2017-03-21T11:58:47Z</dc:date>
    </item>
    <item>
      <title>Re: Log +1 transformations and geometric means</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Log-1-transformations-and-geometric-means/m-p/342927#M18041</link>
      <description>&lt;P&gt;Hi Rick,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you for your response.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I should have clarified. Yes, once the data is transformed, I will be taking the arithmetic mean using PROCSURVEYMEANS. I will be then calculating&amp;nbsp; the geometric mean from that point.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;From a practical standpoint, I was just wondering if there was any difference in the SAS code when doing a log vs log+1 transformation since most guidance out there uses a log transformation -&amp;gt; arithmetic mean -&amp;gt; calculation of geometric mean&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am using this guidance... &lt;A href="https://support.sas.com/rnd/app/stat/examples/SurveyGeoMean/new_example/stat_webex.pdf" target="_blank"&gt;https://support.sas.com/rnd/app/stat/examples/SurveyGeoMean/new_example/stat_webex.pdf&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 21 Mar 2017 14:04:01 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Log-1-transformations-and-geometric-means/m-p/342927#M18041</guid>
      <dc:creator>MVP</dc:creator>
      <dc:date>2017-03-21T14:04:01Z</dc:date>
    </item>
  </channel>
</rss>

