<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803402#M39489</link>
    <description>Thank you all so much for your input.</description>
    <pubDate>Tue, 22 Mar 2022 17:15:47 GMT</pubDate>
    <dc:creator>zaldarsa</dc:creator>
    <dc:date>2022-03-22T17:15:47Z</dc:date>
    <item>
      <title>Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/802891#M39464</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;
&lt;P&gt;I am currently working on this multiple imputation procedure, and all went well except for Proc Mianalyze for Type 3 tests of fixed effects. I have attached my log and code below. Thank you in advance!&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc mixed data=longyr0;
class id tert_meddiet0(ref='0') diabetes0(ref='0')  education0(ref='0') smoke0(ref='0') sex(ref='1') center(ref='1')   ;
model wm=  tert_meddiet0 icv  age0 bmi0 glucose0  hdl0  ldl0 pact0 trig0 dbp0 sbp0 diabetes0  education0  smoke0 sex center tert_meddiet0*time/
s chisq ;
repeated/ type=un subject=id;
by _imputation_;
ods output solutionf=mixedyr0 tests3=pvalyr0 ;
run; quit;

proc mianalyze data=pvalyr0;
class effect;
modeleffects effect;
run;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;LI-CODE lang="sas"&gt;705  proc mianalyze data=pvalyr0;
706  class effect;
707  modeleffects effect;
708  run;

ERROR: The input TYPE= data set is not a valid data set without specifying variables for standard
       errors in the STDERR statement.
NOTE: The SAS System stopped processing this step because of errors.
NOTE: PROCEDURE MIANALYZE used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds


&lt;/LI-CODE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 19 Mar 2022 08:08:08 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/802891#M39464</guid>
      <dc:creator>zaldarsa</dc:creator>
      <dc:date>2022-03-19T08:08:08Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/802898#M39465</link>
      <description>&lt;P&gt;You need specify STDERR statement.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc mianalyze data=pvalyr0;
  class effect;
  modeleffects effect;
stderr  stderr ;
  run;&lt;/CODE&gt;&lt;/PRE&gt;</description>
      <pubDate>Sat, 19 Mar 2022 10:53:11 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/802898#M39465</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2022-03-19T10:53:11Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/802951#M39468</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;
&lt;P&gt;It didn't work because it says that stderr is not in the dataset. Is there another way to go about this without the stderr option?&lt;/P&gt;
&lt;P&gt;Thank you.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;75   proc mianalyze data=pvalyr0;
76   class effect;
77   modeleffects effect;
78   stderr;
79   run;

ERROR: The input TYPE= data set is not a valid data set without specifying variables for standard
       errors in the STDERR statement.
NOTE: The SAS System stopped processing this step because of errors.
NOTE: PROCEDURE MIANALYZE used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
&lt;/PRE&gt;</description>
      <pubDate>Sat, 19 Mar 2022 23:11:04 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/802951#M39468</guid>
      <dc:creator>zaldarsa</dc:creator>
      <dc:date>2022-03-19T23:11:04Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/802968#M39469</link>
      <description>&lt;P&gt;You missed a STDERR variable named stderr . or you could open your dataset and see which variable stands for stderr .&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;proc mianalyze data=pvalyr0;
  class effect;
  modeleffects effect;
stderr  &lt;FONT size="6" color="#FF0000"&gt;&lt;STRONG&gt;stderr&lt;/STRONG&gt;&lt;/FONT&gt; ;
  run;&lt;/PRE&gt;
&lt;P&gt;BTW, if there are no stderr variable in dataset, you can not play it with proc mianalyze.&lt;/P&gt;
&lt;P&gt;I checked your test3= dataset, there is no stderr ,so you can't do it with proc mianalyze .&lt;/P&gt;</description>
      <pubDate>Sun, 20 Mar 2022 09:48:44 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/802968#M39469</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2022-03-20T09:48:44Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803079#M39477</link>
      <description>&lt;P&gt;Have you tried passing the parameter estimates to MIANALYZE?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;That would look like see this example: :&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc mianalyze parms(classvar=full)=mixedyr0;
class id tert_meddiet0(ref='0') diabetes0(ref='0')  education0(ref='0') smoke0(ref='0') sex(ref='1') center(ref='1');
modeleffects intercept tert_meddiet0 icv  age0 bmi0 glucose0  hdl0  ldl0 pact0 trig0 dbp0 sbp0 diabetes0  education0  smoke0 sex center tert_meddiet0*time;
run;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;This follows the example at&amp;nbsp;&lt;A href="https://documentation.sas.com/doc/en/pgmsascdc/9.4_3.3/statug/statug_mianalyze_examples08.htm" target="_self"&gt;https://documentation.sas.com/doc/en/pgmsascdc/9.4_3.3/statug/statug_mianalyze_examples08.htm&lt;/A&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;SteveDenham&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 21 Mar 2022 14:06:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803079#M39477</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2022-03-21T14:06:22Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803084#M39478</link>
      <description>&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csF53863FF"&gt;As far as the Type3 test is concerned, unfortunately, there is no way currently to combine Type3 or CONTRAST tests from MIXED. &amp;nbsp;I have not come across any papers presenting a general methodology on how this could be done. &amp;nbsp;If you happen to find a reference, I would appreciate you passing it along.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csF53863FF"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csF53863FF"&gt;From a syntax point of view, you could dummy code the CLASS variable prior to running Proc MIXED and then use the TEST statement in Proc MIANALYZE to get an overall test. &amp;nbsp;&amp;nbsp;Something like the example below would at least show you how it would be coded.&amp;nbsp; But this approach&amp;nbsp;&lt;STRONG&gt;assumes that doing so would be statistically valid, which no one to my knowledge has verified.&amp;nbsp; &amp;nbsp;&lt;/STRONG&gt;It essentially treats them as it would any other joint test for parameters and applies the multivariate approach of joint tests using multiply imputed data.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csF53863FF"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csF53863FF"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csF53863FF"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN class="csA69FA0E7"&gt;/*Creating Sample Data--Assume that the imputation has already been performed*/&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="cs185F31A1"&gt;data&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;test;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;do&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;_imputation_=&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;1&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;to&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;5&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;do&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;rep=&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;1&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;to&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;100&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;do&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;x=&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;1&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;to&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;3&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;do&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;z=&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;1&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;to&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;2&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;y=-&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;2&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;+&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;.2&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;*x-&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;.2&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;*z+&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;1.6&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;*x*z+rannor(&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;123&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;);&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;output&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;end&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;end&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;end&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;end&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="cs185F31A1"&gt;run&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csA69FA0E7"&gt;/*Create the Dummy variables and interactions for X and Z*/&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="cs185F31A1"&gt;data&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;test;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;set&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;test;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;x1=(x=&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;1&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;);&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;x2=(x=&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;2&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;);&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;z1=(z=&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;1&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;);&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;x1z1=x1*z1;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;x2z1=x2*z1;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="cs185F31A1"&gt;run&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="cs185F31A1"&gt;proc&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="cs185F31A1"&gt;mixed&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;data&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;=test;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;by&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;_imputation_;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;model&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;y=x1 x2 z1 x1z1 x2z1/&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;solution&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;covb&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;ods&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;output&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;SolutionF=parms covb=covb;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="cs185F31A1"&gt;run&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="cs185F31A1"&gt;proc&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="cs185F31A1"&gt;mianalyze&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;parms&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;=parms covb(effectvar=rowcol)=covb;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csFFC69CCF"&gt;modeleffects&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;Intercept x1 x2 z1 x1z1 x2z1;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="csBBCF030F"&gt;interaxntest:&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;test&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;x1z1=&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;0&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;, x2z1=&lt;/SPAN&gt;&lt;SPAN class="cs30C8E4C9"&gt;0&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;/&lt;/SPAN&gt;&lt;SPAN class="csFFC69CCF"&gt;mult&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="cs2654AE3A"&gt;&lt;SPAN class="cs185F31A1"&gt;run&lt;/SPAN&gt;&lt;SPAN class="csBBCF030F"&gt;;&lt;/SPAN&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 21 Mar 2022 14:45:56 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803084#M39478</guid>
      <dc:creator>SAS_Rob</dc:creator>
      <dc:date>2022-03-21T14:45:56Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803320#M39482</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;
&lt;P&gt;OP want combine Type 3 ANOVA table as following, As far as I know it is impossible since there is no stderr for F value ,right ?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Ksharp_0-1647952046631.png" style="width: 400px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/69678i8E58F8862D8F37C8/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Ksharp_0-1647952046631.png" alt="Ksharp_0-1647952046631.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 22 Mar 2022 12:27:39 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803320#M39482</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2022-03-22T12:27:39Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803321#M39483</link>
      <description>Hi Steve,&lt;BR /&gt;That is a parameter estimated table , NOT type3 ANOVA table, OP want ANOVA table I guess .</description>
      <pubDate>Tue, 22 Mar 2022 12:30:04 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803321#M39483</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2022-03-22T12:30:04Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803326#M39484</link>
      <description>&lt;P&gt;Correct.&amp;nbsp; You would have to create the joint tests for the Type 3 hypotheses by using the Parameter Estimates and the TEST statement in MIANALYZE.&lt;/P&gt;</description>
      <pubDate>Tue, 22 Mar 2022 12:42:29 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803326#M39484</guid>
      <dc:creator>SAS_Rob</dc:creator>
      <dc:date>2022-03-22T12:42:29Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803330#M39486</link>
      <description>Could you show code to get the combined F value and Pr&amp;gt;F ?</description>
      <pubDate>Tue, 22 Mar 2022 12:58:06 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803330#M39486</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2022-03-22T12:58:06Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803332#M39487</link>
      <description>&lt;P&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/18408"&gt;@Ksharp&lt;/a&gt;&amp;nbsp;--see my reply above.&amp;nbsp; There isn't a way to combine the F-statistics.&amp;nbsp; What I was proposing was a way to get combined tests based on Type3 hypotheses, but there is not a widely accepted way in the literature to combine the actual F-statistics the way there is to combine Chi-Squares.&lt;/P&gt;</description>
      <pubDate>Tue, 22 Mar 2022 13:01:10 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803332#M39487</guid>
      <dc:creator>SAS_Rob</dc:creator>
      <dc:date>2022-03-22T13:01:10Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Mixed Multiple Imputation: Type 3 tests of fixed effects</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803402#M39489</link>
      <description>Thank you all so much for your input.</description>
      <pubDate>Tue, 22 Mar 2022 17:15:47 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Mixed-Multiple-Imputation-Type-3-tests-of-fixed-effects/m-p/803402#M39489</guid>
      <dc:creator>zaldarsa</dc:creator>
      <dc:date>2022-03-22T17:15:47Z</dc:date>
    </item>
  </channel>
</rss>

