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    <title>topic Re: power calculation for counts in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88302#M4324</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi Steve,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Suppose I log transform the data, do you then suggest that I could treat my data as if normal?&lt;/P&gt;&lt;P&gt;Then proc glmpower would work.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Katrien&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Thu, 09 Aug 2012 11:41:35 GMT</pubDate>
    <dc:creator>kverschueren</dc:creator>
    <dc:date>2012-08-09T11:41:35Z</dc:date>
    <item>
      <title>power calculation for counts</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88300#M4322</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;I have three groups that I compare with a different count as outcome.&lt;/P&gt;&lt;P&gt;I would like to calculate the power for this comparison.&lt;/P&gt;&lt;P&gt;I was thinking of proc glmpower and using Poisson as link function.&lt;/P&gt;&lt;P&gt;However this is not supported.&lt;/P&gt;&lt;P&gt;Is there a macro written and available for use that would be able to support my question?&lt;/P&gt;&lt;P&gt;Thanks, Katrien&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 09 Aug 2012 08:32:11 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88300#M4322</guid>
      <dc:creator>kverschueren</dc:creator>
      <dc:date>2012-08-09T08:32:11Z</dc:date>
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    <item>
      <title>Re: power calculation for counts</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88301#M4323</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;You could try transforming your data prior to using glmpower.&amp;nbsp; Since the analysis for the Poisson defaults to a log link, that seems like a logical first choice.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 09 Aug 2012 11:19:56 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88301#M4323</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2012-08-09T11:19:56Z</dc:date>
    </item>
    <item>
      <title>Re: power calculation for counts</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88302#M4324</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi Steve,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Suppose I log transform the data, do you then suggest that I could treat my data as if normal?&lt;/P&gt;&lt;P&gt;Then proc glmpower would work.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Katrien&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 09 Aug 2012 11:41:35 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88302#M4324</guid>
      <dc:creator>kverschueren</dc:creator>
      <dc:date>2012-08-09T11:41:35Z</dc:date>
    </item>
    <item>
      <title>Re: power calculation for counts</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88303#M4325</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;That is one of the assumptions behind the link function--that it normalizes the data.&amp;nbsp; For years before good maximum likelihood algorithms existed, data were transformed to meet normality assumptions.&amp;nbsp; Actually, the preferred transformation for count data was a square root transformation (Sokal and Rohlf, &lt;EM&gt;Biometry, &lt;/EM&gt;1969).&amp;nbsp; However, since you indicate that you will probably be analyzing the data using one of SAS's generalized linear model procedures (dist=poisson), and the Poisson distribution defaults to a log link, I suggested transforming using the log.&amp;nbsp; &lt;STRONG&gt;Warning&lt;/STRONG&gt;: If you have zeroes in your dependent variable, you probably ought to transform as log(y + 1). You may want to do some data exploration to check the assumption of having a Poisson distribution (e.g. are the mean and variance approximately equal?, are the data over-represented with zeroes?).&amp;nbsp; You could find yourself wanting to use a negative binomial distribution (variance&amp;gt;mean) or a zero-inflated Poisson or negative binomial.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;An alternative to the log transform would be to use the square root transformation prior to GLMPOWER, and analyze with&amp;nbsp; LINK=POWER(0.5).&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Good luck.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 09 Aug 2012 12:06:53 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88303#M4325</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2012-08-09T12:06:53Z</dc:date>
    </item>
    <item>
      <title>Re: power calculation for counts</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88304#M4326</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thanks a lot Steve. I will proceed as you suggest.&lt;/P&gt;&lt;P&gt;Nice day, Katrien&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 09 Aug 2012 12:19:03 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/power-calculation-for-counts/m-p/88304#M4326</guid>
      <dc:creator>kverschueren</dc:creator>
      <dc:date>2012-08-09T12:19:03Z</dc:date>
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