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    <title>topic Re: PROC GENMOD - Probabilities for each &amp;quot;response level&amp;quot; by &amp;quot;treatment&amp;quot; in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD-Probabilities-for-each-quot-response-level-quot-by/m-p/100390#M5180</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Nick,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;What about interval estimates?&amp;nbsp; You could get these by adding the cl option after the slash.&amp;nbsp; Approximate standard errors are a lot harder.&amp;nbsp; While the delta method is by far to be preferred, one approach would be to estimate the standard error as sqrt( estimate * (1 - estimate) / df)).&amp;nbsp; This means post-processing of the estimates dataset using ODS output estimates=estimates;&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>Wed, 25 Jul 2012 14:28:12 GMT</pubDate>
    <dc:creator>SteveDenham</dc:creator>
    <dc:date>2012-07-25T14:28:12Z</dc:date>
    <item>
      <title>PROC GENMOD - Probabilities for each "response level" by "treatment"</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD-Probabilities-for-each-quot-response-level-quot-by/m-p/100387#M5177</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I would like to get the probability of having any "response level" for each level of "treatment" in my data, and not only the "probabilities of levels of y having LOWER Ordered Values in the&lt;/P&gt;&lt;P&gt;response profile table." that SAS automatically outputs.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;(I'm simplifying a lot the real scenario just to have an idea).&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Let's say I would like to see the effect of 3 treatments (T1, T2 and T3) on a given health status (5 categories: low, mid-low, med, mid-high and high), correcting for the covariate Weight (W).&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I'm running an ordinal multinomial model:&lt;/P&gt;&lt;P&gt;----------------------------------------------------------------------------------&lt;/P&gt;&lt;P&gt;proc genmod data=health;&lt;/P&gt;&lt;P&gt;class T;&lt;/P&gt;&lt;P&gt;model Status = T W/dist=multinomial link=clogit type3;&lt;/P&gt;&lt;P&gt;estimate 'T1 - T2' T 1 -1/exp;&lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;P&gt;---------------------------------------------------------------------------&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;This (estimate statement) code gives that the odds of T1 being in lower health categories is 2.8 the odds of T2 being in lower health categories.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Although this is interesting, that's not what I want. What I really want are all the probabilities of being in each of the 5 Health Categories for each of the 3 Treatments:&lt;/P&gt;&lt;P&gt;P(low|T1)&lt;/P&gt;&lt;P&gt;P(mid-low|T1)&lt;/P&gt;&lt;P&gt;...&lt;/P&gt;&lt;P&gt;P(high|T3).&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Is is possible to have this in Proc Genmod? If so, can anyone help me?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Nick&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 05 Jul 2012 18:11:33 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD-Probabilities-for-each-quot-response-level-quot-by/m-p/100387#M5177</guid>
      <dc:creator>Nick_Serao</dc:creator>
      <dc:date>2012-07-05T18:11:33Z</dc:date>
    </item>
    <item>
      <title>Re: PROC GENMOD - Probabilities for each "response level" by "treatment"</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD-Probabilities-for-each-quot-response-level-quot-by/m-p/100388#M5178</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Not sure this will give what you want, but it might lead to it:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc genmod data=health;&lt;/P&gt;&lt;P&gt;class T;&lt;/P&gt;&lt;P&gt;model Status = T W/dist=multinomial link=clogit type3 aggregate=T;&lt;/P&gt;&lt;P&gt;estimate 'P(low|T1)' intercept 1 T 1 0 0 / exp e;&lt;/P&gt;&lt;P&gt;estimate 'P(mid-low, low|T1) intercept 0 1&amp;nbsp; T 1 0 0 / exp e;&lt;/P&gt;&lt;P&gt;estimate 'P(med, mid-low, low|T1) intercept 0 0 1&amp;nbsp; T 1 0 0 / exp e;&lt;/P&gt;&lt;P&gt;&amp;lt;put more estimates in here, as needed, following these examples&amp;gt;&lt;/P&gt;&lt;P&gt;ods output estimates=estimates;&lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I based it on the cumulative logit.&amp;nbsp; There would have to be a post-processing step on the estimates dataset, as the mean estimates are the cumulative probabilities.&amp;nbsp; The estimated probabilities per level would have to be calculated by difference, with the probability of the 'high' level as 1 - P(med-high, med, mid-low, low|T1).&amp;nbsp; Unfortunately, this will not give standard errors for the probabilities, but if you only need point estimates, this might be an approach you could use.&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>Fri, 06 Jul 2012 11:19:16 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD-Probabilities-for-each-quot-response-level-quot-by/m-p/100388#M5178</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2012-07-06T11:19:16Z</dc:date>
    </item>
    <item>
      <title>Re: PROC GENMOD - Probabilities for each "response level" by "treatment"</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD-Probabilities-for-each-quot-response-level-quot-by/m-p/100389#M5179</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thanks Steve...&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Sorry for the late reply, I was travelling...&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;This was actually the first approach I tried, but I was not having much success with these estimates because my model is a little bit more complex, but looking at your code, I could finally understand what I had to do.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;But, as you said, I could only get the point estimates.&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 25 Jul 2012 14:09:40 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD-Probabilities-for-each-quot-response-level-quot-by/m-p/100389#M5179</guid>
      <dc:creator>Nick_Serao</dc:creator>
      <dc:date>2012-07-25T14:09:40Z</dc:date>
    </item>
    <item>
      <title>Re: PROC GENMOD - Probabilities for each "response level" by "treatment"</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD-Probabilities-for-each-quot-response-level-quot-by/m-p/100390#M5180</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Nick,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;What about interval estimates?&amp;nbsp; You could get these by adding the cl option after the slash.&amp;nbsp; Approximate standard errors are a lot harder.&amp;nbsp; While the delta method is by far to be preferred, one approach would be to estimate the standard error as sqrt( estimate * (1 - estimate) / df)).&amp;nbsp; This means post-processing of the estimates dataset using ODS output estimates=estimates;&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>Wed, 25 Jul 2012 14:28:12 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD-Probabilities-for-each-quot-response-level-quot-by/m-p/100390#M5180</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2012-07-25T14:28:12Z</dc:date>
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