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    <title>topic Re: Power analysis for Poisson regression in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Power-analysis-for-Poisson-regression/m-p/841350#M41715</link>
    <description>&lt;P&gt;You can use the &lt;A href="https://go.documentation.sas.com/doc/en/pgmsascdc/default/statug/statug_power_syntax08.htm" target="_self"&gt;CUSTOM statement&lt;/A&gt; in PROC POWER, and there's an example in &lt;A href="https://www.sas.com/content/dam/SAS/support/en/sas-global-forum-proceedings/2018/1983-2018.pdf" target="_self"&gt;this paper&lt;/A&gt; from SAS Global Forum 2018. The main example involves logistic regression, but the section "Steps for a Poisson Regression Alternative" at the bottom of page 12 describes how to adapt it to a Poisson regression.&lt;/P&gt;</description>
    <pubDate>Fri, 28 Oct 2022 16:53:19 GMT</pubDate>
    <dc:creator>John_Castelloe</dc:creator>
    <dc:date>2022-10-28T16:53:19Z</dc:date>
    <item>
      <title>Power analysis for Poisson regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Power-analysis-for-Poisson-regression/m-p/839003#M41542</link>
      <description>&lt;P&gt;Hi all, I'm trying to get a power analysis for a health care study that will evaluate incidence rate ratio of an event (predicted variable as counts and few categorical and continuous independent predictors). I tried to find a way to do it in SAS, but I can't seems to find the right code.&amp;nbsp;&lt;/P&gt;&lt;P&gt;I tried Cox Regression, code below, but I'm not sure if this will give me the same power results as those estimating for Poisson regression, as one takes into account time to event and the other the counts or rates only...any suggestions on how to proceed ? Thanks.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;ods noproctitle;&lt;BR /&gt;ods graphics / imagemap=on;&lt;/P&gt;&lt;P&gt;proc power;&lt;BR /&gt;coxreg test=score sides=2 ntotal=13000 eventprob=0.017 alpha=0.05&lt;BR /&gt;hazardratio=1.2 1.5 rsquare=0 0.3 stddev=1.1 power=.;&lt;BR /&gt;plot x=n;&lt;BR /&gt;run;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 17 Oct 2022 15:19:31 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Power-analysis-for-Poisson-regression/m-p/839003#M41542</guid>
      <dc:creator>gtrifan</dc:creator>
      <dc:date>2022-10-17T15:19:31Z</dc:date>
    </item>
    <item>
      <title>Re: Power analysis for Poisson regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Power-analysis-for-Poisson-regression/m-p/841350#M41715</link>
      <description>&lt;P&gt;You can use the &lt;A href="https://go.documentation.sas.com/doc/en/pgmsascdc/default/statug/statug_power_syntax08.htm" target="_self"&gt;CUSTOM statement&lt;/A&gt; in PROC POWER, and there's an example in &lt;A href="https://www.sas.com/content/dam/SAS/support/en/sas-global-forum-proceedings/2018/1983-2018.pdf" target="_self"&gt;this paper&lt;/A&gt; from SAS Global Forum 2018. The main example involves logistic regression, but the section "Steps for a Poisson Regression Alternative" at the bottom of page 12 describes how to adapt it to a Poisson regression.&lt;/P&gt;</description>
      <pubDate>Fri, 28 Oct 2022 16:53:19 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Power-analysis-for-Poisson-regression/m-p/841350#M41715</guid>
      <dc:creator>John_Castelloe</dc:creator>
      <dc:date>2022-10-28T16:53:19Z</dc:date>
    </item>
    <item>
      <title>Re: Power analysis for Poisson regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Power-analysis-for-Poisson-regression/m-p/841359#M41716</link>
      <description>&lt;P&gt;Thank you!&lt;/P&gt;</description>
      <pubDate>Fri, 28 Oct 2022 17:39:43 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Power-analysis-for-Poisson-regression/m-p/841359#M41716</guid>
      <dc:creator>gtrifan</dc:creator>
      <dc:date>2022-10-28T17:39:43Z</dc:date>
    </item>
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