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    <title>topic Re: PROC MIANALYZE procedure after PROC GLIMMIX binary outcome (NO odds ratio and CL) in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-MIANALYZE-procedure-after-PROC-GLIMMIX-binary-outcome-NO/m-p/608713#M29493</link>
    <description>&lt;P&gt;You likely have a WARNING message in your LOG regarding the between imputation variance being zero.&amp;nbsp; This essentially means that the estimates for each of the imputations is identical.&amp;nbsp;&amp;nbsp;&lt;SPAN&gt;When the between imputation variance is zero then the number of Degrees of Freedom is undefined so you cannot get a confidence interval or p-values.&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;Unfortunately, there is not a good approach to take in this case. This is one of the limitations of multiple imputation in general. You might try doing a literature search to see if you can find any references that deal with this issue.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Because GLIMMIX does not report a standard error for the odds ratio directly, you would not be able to combine those either.&amp;nbsp; I suspect you would run into the same issue with the between imputation variance anyway.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Normally you would combine the log (OR), that is the parameter estimates, and then exponentiate those values in a subsequent data step.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Mon, 02 Dec 2019 14:48:45 GMT</pubDate>
    <dc:creator>SAS_Rob</dc:creator>
    <dc:date>2019-12-02T14:48:45Z</dc:date>
    <item>
      <title>PROC MIANALYZE procedure after PROC GLIMMIX binary outcome (NO odds ratio and CL)</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-MIANALYZE-procedure-after-PROC-GLIMMIX-binary-outcome-NO/m-p/608246#M29492</link>
      <description>&lt;P&gt;Hi SAS users,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I used Multiple imputation with GLIMMIX for binary outcome variable with one binary independent variable (as example).&amp;nbsp; When I ran PROC MIANALYZE, the results only showed the estimate and SE but did not show 95% CL nor the significance (attach pic of the table). Also did not provides the odds ratio table.&amp;nbsp; &amp;nbsp;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I used the following code:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;PROC GLIMMIX DATA=shis.shis_mi3 METHOD=QUAD empirical=classical;&lt;BR /&gt;CLASS rgn_code SEX1 (ref=FIRST);&lt;BR /&gt;MODEL PA (EVENT=LAST)= SEX1 /CL DIST=BINARY LINK=LOGIT SOLUTION&lt;BR /&gt;ODDSRATIO (DIFF=LAST LABEL);&amp;nbsp;&lt;BR /&gt;RANDOM INTERCEPT / SUBJECT=rgn_code S CL TYPE=VC;&lt;BR /&gt;by imputation_;&lt;BR /&gt;nloptions gconv=0;&lt;BR /&gt;ods output ParameterEstimates=PAparm1;&lt;BR /&gt;COVTEST /WALD;&lt;BR /&gt;RUN;&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;/* Prepare pooled estimates for MI (excluding original unimputed data) */&lt;BR /&gt;data imputed;&lt;BR /&gt;set PAparm1;&lt;BR /&gt;_imputation_=imputation_;&lt;BR /&gt;If _imputation_&amp;gt;0;&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;/* Calculate and print pooled estimates for MI */&lt;BR /&gt;proc mianalyze parms = imputed;&lt;BR /&gt;CLASS SEX1;&lt;BR /&gt;modeleffects Intercept SEX1;&lt;BR /&gt;run;&lt;/P&gt;</description>
      <pubDate>Fri, 29 Nov 2019 13:44:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-MIANALYZE-procedure-after-PROC-GLIMMIX-binary-outcome-NO/m-p/608246#M29492</guid>
      <dc:creator>mtechnologist</dc:creator>
      <dc:date>2019-11-29T13:44:22Z</dc:date>
    </item>
    <item>
      <title>Re: PROC MIANALYZE procedure after PROC GLIMMIX binary outcome (NO odds ratio and CL)</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-MIANALYZE-procedure-after-PROC-GLIMMIX-binary-outcome-NO/m-p/608713#M29493</link>
      <description>&lt;P&gt;You likely have a WARNING message in your LOG regarding the between imputation variance being zero.&amp;nbsp; This essentially means that the estimates for each of the imputations is identical.&amp;nbsp;&amp;nbsp;&lt;SPAN&gt;When the between imputation variance is zero then the number of Degrees of Freedom is undefined so you cannot get a confidence interval or p-values.&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;Unfortunately, there is not a good approach to take in this case. This is one of the limitations of multiple imputation in general. You might try doing a literature search to see if you can find any references that deal with this issue.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Because GLIMMIX does not report a standard error for the odds ratio directly, you would not be able to combine those either.&amp;nbsp; I suspect you would run into the same issue with the between imputation variance anyway.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Normally you would combine the log (OR), that is the parameter estimates, and then exponentiate those values in a subsequent data step.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 02 Dec 2019 14:48:45 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-MIANALYZE-procedure-after-PROC-GLIMMIX-binary-outcome-NO/m-p/608713#M29493</guid>
      <dc:creator>SAS_Rob</dc:creator>
      <dc:date>2019-12-02T14:48:45Z</dc:date>
    </item>
    <item>
      <title>Re: PROC MIANALYZE procedure after PROC GLIMMIX binary outcome (NO odds ratio and CL)</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-MIANALYZE-procedure-after-PROC-GLIMMIX-binary-outcome-NO/m-p/608899#M29495</link>
      <description>Well explained Rob. Thanks.</description>
      <pubDate>Tue, 03 Dec 2019 00:24:14 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-MIANALYZE-procedure-after-PROC-GLIMMIX-binary-outcome-NO/m-p/608899#M29495</guid>
      <dc:creator>mtechnologist</dc:creator>
      <dc:date>2019-12-03T00:24:14Z</dc:date>
    </item>
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