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    <title>topic PROC GENMOD in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD/m-p/328504#M17320</link>
    <description>&lt;P&gt;Hello,&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;May you help with the GENMOD procedure? &amp;nbsp;Thank you .&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;proc genmod data= noshare descend;&lt;BR /&gt;class PatientID gender region race ethnicity PracticeSize LineNumber DrugName num_drugs ;&lt;BR /&gt;model y =age gender region race ethnicity weight_kg BSA_mm PracticeSize LineNumber num_admin_line DrugName num_drugs /&lt;BR /&gt;dist=bin link=logit noscale;&lt;BR /&gt;repeated subject=PatientID/type=un ;&lt;BR /&gt;run;&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;proc genmod data= noshare descend;&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;class PatientID gender region race ethnicity PracticeSize LineNumber DrugName num_drugs ;&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;model y =age gender region race ethnicity weight_kg BSA_mm PracticeSize LineNumber num_admin_line DrugName num_drugs /&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;dist=bin link=logit noscale;&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;repeated subject=PatientID/type=un ;&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;run;&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;I have a data set with mutiple observations per patinets , observerded at different time point for different patient, with "Y/N" response. There are 8000 patients with &amp;nbsp;60000 observations at mutiple centers. &amp;nbsp;My questions:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;1. Should GENMOD be used for this correlated data ? &amp;nbsp;Centers , patients id are correlated.&amp;nbsp;&lt;/P&gt;&lt;P&gt;2. &amp;nbsp;What the error means after I ran the above procedure ? &amp;nbsp;Any way I can fix it ?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;131 proc genmod data= noshare descend;&lt;BR /&gt;132 class PatientID gender region race ethnicity PracticeSize_Overall LineNumber DrugName&lt;BR /&gt;132! num_drugs ;&lt;BR /&gt;133 model y =age gender region race ethnicity weight_kg BSA_mm PracticeSize_Overall LineNumber&lt;BR /&gt;133! num_admin_line DrugName num_drugs /&lt;BR /&gt;134 dist=bin link=logit noscale;&lt;BR /&gt;135 repeated subject=PatientID/type=un ;&lt;BR /&gt;136 run;&lt;/P&gt;&lt;P&gt;NOTE: Class levels for some variables were not printed due to excessive size.&lt;BR /&gt;NOTE: PROC GENMOD is modeling the probability that y='1'.&lt;BR /&gt;NOTE: Algorithm converged.&lt;BR /&gt;WARNING: The number of response pairs for estimating correlation is less than or equal to the&lt;BR /&gt;number of regression parameters. A simpler correlation model might be more appropriate.&lt;BR /&gt;NOTE: The working correlation has been ridged with a maximum value of 8.805289195 to avoid&lt;BR /&gt;singularity.&lt;BR /&gt;ERROR: Error in computing the variance function.&lt;BR /&gt;ERROR: Error in parameter estimate covariance computation.&lt;BR /&gt;ERROR: Error in estimation routine.&lt;BR /&gt;NOTE: The SAS System stopped processing this step because of errors.&lt;BR /&gt;NOTE: The PROCEDURE GENMOD printed pages 129-135.&lt;BR /&gt;NOTE: PROCEDURE GENMOD used (Total process time):&lt;BR /&gt;real time 3.38 seconds&lt;BR /&gt;cpu time 3.37 seconds&lt;/P&gt;&lt;P&gt;NOTE: Remote submit to D.__4018 complete&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you very much,&lt;/P&gt;&lt;P&gt;Ivy&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Mon, 30 Jan 2017 16:45:27 GMT</pubDate>
    <dc:creator>Ivy</dc:creator>
    <dc:date>2017-01-30T16:45:27Z</dc:date>
    <item>
      <title>PROC GENMOD</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD/m-p/328504#M17320</link>
      <description>&lt;P&gt;Hello,&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;May you help with the GENMOD procedure? &amp;nbsp;Thank you .&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;proc genmod data= noshare descend;&lt;BR /&gt;class PatientID gender region race ethnicity PracticeSize LineNumber DrugName num_drugs ;&lt;BR /&gt;model y =age gender region race ethnicity weight_kg BSA_mm PracticeSize LineNumber num_admin_line DrugName num_drugs /&lt;BR /&gt;dist=bin link=logit noscale;&lt;BR /&gt;repeated subject=PatientID/type=un ;&lt;BR /&gt;run;&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;proc genmod data= noshare descend;&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;class PatientID gender region race ethnicity PracticeSize LineNumber DrugName num_drugs ;&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;model y =age gender region race ethnicity weight_kg BSA_mm PracticeSize LineNumber num_admin_line DrugName num_drugs /&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;dist=bin link=logit noscale;&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;repeated subject=PatientID/type=un ;&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;run;&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;I have a data set with mutiple observations per patinets , observerded at different time point for different patient, with "Y/N" response. There are 8000 patients with &amp;nbsp;60000 observations at mutiple centers. &amp;nbsp;My questions:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;1. Should GENMOD be used for this correlated data ? &amp;nbsp;Centers , patients id are correlated.&amp;nbsp;&lt;/P&gt;&lt;P&gt;2. &amp;nbsp;What the error means after I ran the above procedure ? &amp;nbsp;Any way I can fix it ?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;131 proc genmod data= noshare descend;&lt;BR /&gt;132 class PatientID gender region race ethnicity PracticeSize_Overall LineNumber DrugName&lt;BR /&gt;132! num_drugs ;&lt;BR /&gt;133 model y =age gender region race ethnicity weight_kg BSA_mm PracticeSize_Overall LineNumber&lt;BR /&gt;133! num_admin_line DrugName num_drugs /&lt;BR /&gt;134 dist=bin link=logit noscale;&lt;BR /&gt;135 repeated subject=PatientID/type=un ;&lt;BR /&gt;136 run;&lt;/P&gt;&lt;P&gt;NOTE: Class levels for some variables were not printed due to excessive size.&lt;BR /&gt;NOTE: PROC GENMOD is modeling the probability that y='1'.&lt;BR /&gt;NOTE: Algorithm converged.&lt;BR /&gt;WARNING: The number of response pairs for estimating correlation is less than or equal to the&lt;BR /&gt;number of regression parameters. A simpler correlation model might be more appropriate.&lt;BR /&gt;NOTE: The working correlation has been ridged with a maximum value of 8.805289195 to avoid&lt;BR /&gt;singularity.&lt;BR /&gt;ERROR: Error in computing the variance function.&lt;BR /&gt;ERROR: Error in parameter estimate covariance computation.&lt;BR /&gt;ERROR: Error in estimation routine.&lt;BR /&gt;NOTE: The SAS System stopped processing this step because of errors.&lt;BR /&gt;NOTE: The PROCEDURE GENMOD printed pages 129-135.&lt;BR /&gt;NOTE: PROCEDURE GENMOD used (Total process time):&lt;BR /&gt;real time 3.38 seconds&lt;BR /&gt;cpu time 3.37 seconds&lt;/P&gt;&lt;P&gt;NOTE: Remote submit to D.__4018 complete&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you very much,&lt;/P&gt;&lt;P&gt;Ivy&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 30 Jan 2017 16:45:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD/m-p/328504#M17320</guid>
      <dc:creator>Ivy</dc:creator>
      <dc:date>2017-01-30T16:45:27Z</dc:date>
    </item>
    <item>
      <title>Re: PROC GENMOD</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD/m-p/329074#M17363</link>
      <description>&lt;P&gt;The warning comes about from the fact that you have more levels in all of your independent variables than you have observations. &amp;nbsp;You will have to reduce your model in some fashion--in particular, fitting an unstructured working covariance leads to n*(n-1)/2 parameters to estimate in addition to all of the independent parameters.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;On a different note, if you wish to accommodate the clustering implied by site and patient, you should consider using PROC GLIMMIX, with those as random effects. &amp;nbsp;There is a lot of material both here and elsewhere on the web regarding good code for that approach. &amp;nbsp;Still, the key is identifying a tractable model.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Steve Denham&lt;/P&gt;</description>
      <pubDate>Wed, 01 Feb 2017 13:13:45 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-GENMOD/m-p/329074#M17363</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2017-02-01T13:13:45Z</dc:date>
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