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    <title>topic Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577792#M28381</link>
    <description>&lt;P&gt;I calculated "means" for age, bmi, _ps_ and the "weighted means" based on the products&amp;nbsp; _ATEWgt_ *(age, bmi, and _ps_)&amp;nbsp;using PROC MEANS.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;All the "means" match the means in the tables but none of my "weighted means", even though the sums of _ATEWgt_ match the ones in the tables for each drug.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Apparently, _ATEWgt_ was not supposed to be used as the multiplier to get the weighted means. Then, how to get the weighted means?&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;</description>
    <pubDate>Tue, 30 Jul 2019 15:29:58 GMT</pubDate>
    <dc:creator>withyin</dc:creator>
    <dc:date>2019-07-30T15:29:58Z</dc:date>
    <item>
      <title>PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577787#M28380</link>
      <description>&lt;P&gt;&lt;FONT size="2"&gt;In "Example 98.1 Propensity Score Weighting", how did SAS calculate the weighted means 0.2454 and 0.2381 in Table "&lt;SPAN&gt;Output 98.1.2: Propensity Score Information"?&amp;nbsp; Or all the weighted means in Table "Output 98.1.3: Variable Information"?&amp;nbsp;&lt;/SPAN&gt;&lt;/FONT&gt;&lt;/P&gt;&lt;P&gt;&lt;A href="https://documentation.sas.com/?docsetId=statug&amp;amp;docsetTarget=statug_psmatch_examples01.htm&amp;amp;docsetVersion=15.1&amp;amp;locale=en"&gt;https://documentation.sas.com/?docsetId=statug&amp;amp;docsetTarget=statug_psmatch_examples01.htm&amp;amp;docsetVersion=15.1&amp;amp;locale=en&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;I got the weights 460.45 and&amp;nbsp;489.59 as the sums of _ATEWgt_ for Drug_X and Drug_A respectively in both tables. But multiplying _ATEWgt_ with age, BMI, or _ps_ could not give me the same weighted means in those tables.&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;I was trying to use the _ATEWgt_ (in a survival analysis) as the weight for PROC PHREG. Because of the uncertainty I felt from the experience above, I am not sure whether I can use _ATEWgt_ as the weight in PROC PHREG.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Thank you for your help!&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 30 Jul 2019 15:15:05 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577787#M28380</guid>
      <dc:creator>withyin</dc:creator>
      <dc:date>2019-07-30T15:15:05Z</dc:date>
    </item>
    <item>
      <title>Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577792#M28381</link>
      <description>&lt;P&gt;I calculated "means" for age, bmi, _ps_ and the "weighted means" based on the products&amp;nbsp; _ATEWgt_ *(age, bmi, and _ps_)&amp;nbsp;using PROC MEANS.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;All the "means" match the means in the tables but none of my "weighted means", even though the sums of _ATEWgt_ match the ones in the tables for each drug.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Apparently, _ATEWgt_ was not supposed to be used as the multiplier to get the weighted means. Then, how to get the weighted means?&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;</description>
      <pubDate>Tue, 30 Jul 2019 15:29:58 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577792#M28381</guid>
      <dc:creator>withyin</dc:creator>
      <dc:date>2019-07-30T15:29:58Z</dc:date>
    </item>
    <item>
      <title>Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577809#M28382</link>
      <description>&lt;P&gt;Can you post the code you used to find your weighted means?&lt;/P&gt;
&lt;P&gt;To be clear you're using exactly the data in the example, not your customized data, just trying to recreate the results from the documentation?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/283407"&gt;@withyin&lt;/a&gt;&amp;nbsp;wrote:&lt;BR /&gt;
&lt;P&gt;I calculated "means" for age, bmi, _ps_ and the "weighted means" based on the products&amp;nbsp; _ATEWgt_ *(age, bmi, and _ps_)&amp;nbsp;using PROC MEANS.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;All the "means" match the means in the tables but none of my "weighted means", even though the sums of _ATEWgt_ match the ones in the tables for each drug.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Apparently, _ATEWgt_ was not supposed to be used as the multiplier to get the weighted means. Then, how to get the weighted means?&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Thanks!&lt;/P&gt;
&lt;HR /&gt;&lt;/BLOCKQUOTE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 30 Jul 2019 16:17:51 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577809#M28382</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2019-07-30T16:17:51Z</dc:date>
    </item>
    <item>
      <title>Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577815#M28383</link>
      <description>&lt;P&gt;Thank you Reeza for your help.&lt;/P&gt;&lt;P&gt;Here are my codes:&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc psmatch data=drugs region=allobs;
   class Drug Gender;
   psmodel Drug(Treated='Drug_X')= Gender Age BMI;
   psweight weight=atewgt nlargestwgt=6;
   assess lps var=(Gender Age BMI)
          / varinfo plots=(barchart boxplot(display=(lps BMI)) wgtcloud);
   id BMI;
   output out(obs=all)=OutEx1 weight=_ATEWgt_;
run;

data weight;
	set OutEx1;
	age_wt=age*_ATEWgt_;
	bmi_wt=bmi*_ATEWgt_;
	ps_wt=_ps_*_ATEWgt_;
run;
proc sort;
  by drug;
proc means noprint;
  	by drug;
  	var age age_wt bmi bmi_wt _ps_ ps_wt _atewgt_;
  	output out=mean 
	mean=agem age_wtm bmim bmi_wtm _ps_m ps_wtm _atewgtm
	sum=ages age_wts bmis bmi_wts _ps_s ps_wts _atewgts;
run;
proc print;run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;The PROC PSMATCH part (and parts prior that) was copied from Example 98.1.&amp;nbsp;&lt;/P&gt;&lt;P&gt;None of the weighted means (*_wtm) match that in the tables 98.1.2 and 98.1.3, even though _atewgts match the weights in Tables 98.1.2 and 98.1.3.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;</description>
      <pubDate>Tue, 30 Jul 2019 16:33:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577815#M28383</guid>
      <dc:creator>withyin</dc:creator>
      <dc:date>2019-07-30T16:33:09Z</dc:date>
    </item>
    <item>
      <title>Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577820#M28384</link>
      <description>I won't have time to look at this until tonight, so hopefully someone else does, but if I don't remember ping me.</description>
      <pubDate>Tue, 30 Jul 2019 16:49:06 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577820#M28384</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2019-07-30T16:49:06Z</dc:date>
    </item>
    <item>
      <title>Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577823#M28385</link>
      <description>Thanks! Please take a look when you have a chance.&lt;BR /&gt;</description>
      <pubDate>Tue, 30 Jul 2019 17:02:08 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577823#M28385</guid>
      <dc:creator>withyin</dc:creator>
      <dc:date>2019-07-30T17:02:08Z</dc:date>
    </item>
    <item>
      <title>Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577929#M28386</link>
      <description>&lt;P&gt;I didn't end up using your code, not sure what it all does. However, my checks does show that the results do match.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I checked the weighted mean of AGE and BMI and they matched exactly.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;ods graphics off;
ods select psinfo varinfo;
proc psmatch data=drugs region=allobs;
   class Drug Gender;
   psmodel Drug(Treated='Drug_X')= Gender Age BMI;
   psweight weight=atewgt nlargestwgt=6;
   assess lps var=(Gender Age BMI)
          / varinfo;
   id BMI;
   output out(obs=all)=OutEx1 weight=_ATEWgt_;
run;


proc sort data=outex1;
by drug;
run;

proc means data=outex1 N MEAN SUM;
    by drug;
    var age bmi ; 
    weight _atewgt_ ;
    output out=mean 
    mean= sum= / autoname;
run;&lt;/PRE&gt;
&lt;P&gt;Results:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;SECTION data-name="PSMatch" data-sec-type="proc"&gt;
&lt;DIV id="IDX1" class="proc_title_group"&gt;
&lt;P class="c proctitle"&gt;The PSMATCH Procedure&lt;/P&gt;
&lt;/DIV&gt;
&lt;SECTION&gt;
&lt;ARTICLE aria-label="Variable Information"&gt;
&lt;TABLE class="table" aria-label="Variable Information"&gt;&lt;CAPTION aria-label="Variable Information"&gt;&amp;nbsp;&lt;/CAPTION&gt;&lt;COLGROUP&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;/COLGROUP&gt;&lt;COLGROUP&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;/COLGROUP&gt;
&lt;THEAD&gt;
&lt;TR&gt;
&lt;TH class="c b header" colspan="15" scope="colgroup"&gt;Variable Information&lt;/TH&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="b header" rowspan="2" scope="col"&gt;Variable&lt;/TH&gt;
&lt;TH class="b header" rowspan="2" scope="col"&gt;Observations&lt;/TH&gt;
&lt;TH class="c b header" colspan="6" scope="colgroup"&gt;Treated (Drug = Drug_X)&lt;/TH&gt;
&lt;TH class="c b header" colspan="6" scope="colgroup"&gt;Control (Drug = Drug_A)&lt;/TH&gt;
&lt;TH class="c b header" scope="col"&gt;Treated -&lt;BR /&gt;Control&lt;/TH&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="r b header" scope="col"&gt;N&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Weight&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Mean&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Standard&lt;BR /&gt;Deviation&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Minimum&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Maximum&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;N&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Weight&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Mean&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Standard&lt;BR /&gt;Deviation&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Minimum&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Maximum&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Mean&lt;BR /&gt;Difference&lt;/TH&gt;
&lt;/TR&gt;
&lt;/THEAD&gt;
&lt;TBODY&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;Logit Prop Score&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;All&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;-0.88062&lt;/TD&gt;
&lt;TD class="r data"&gt;0.681761&lt;/TD&gt;
&lt;TD class="r data"&gt;-2.74745&lt;/TD&gt;
&lt;TD class="r data"&gt;0.58035&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;-1.52059&lt;/TD&gt;
&lt;TD class="r data"&gt;0.844486&lt;/TD&gt;
&lt;TD class="r data"&gt;-3.88386&lt;/TD&gt;
&lt;TD class="r data"&gt;0.78036&lt;/TD&gt;
&lt;TD class="r data"&gt;0.63997&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;&amp;nbsp;&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;Region&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;-0.88062&lt;/TD&gt;
&lt;TD class="r data"&gt;0.681761&lt;/TD&gt;
&lt;TD class="r data"&gt;-2.74745&lt;/TD&gt;
&lt;TD class="r data"&gt;0.58035&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;-1.52059&lt;/TD&gt;
&lt;TD class="r data"&gt;0.844486&lt;/TD&gt;
&lt;TD class="r data"&gt;-3.88386&lt;/TD&gt;
&lt;TD class="r data"&gt;0.78036&lt;/TD&gt;
&lt;TD class="r data"&gt;0.63997&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;&amp;nbsp;&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;Weighted&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;460.45&lt;/TD&gt;
&lt;TD class="r data"&gt;-1.25406&lt;/TD&gt;
&lt;TD class="r data"&gt;0.741386&lt;/TD&gt;
&lt;TD class="r data"&gt;-2.74745&lt;/TD&gt;
&lt;TD class="r data"&gt;0.58035&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;489.59&lt;/TD&gt;
&lt;TD class="r data"&gt;-1.35103&lt;/TD&gt;
&lt;TD class="r data"&gt;0.894234&lt;/TD&gt;
&lt;TD class="r data"&gt;-3.88386&lt;/TD&gt;
&lt;TD class="r data"&gt;0.78036&lt;/TD&gt;
&lt;TD class="r data"&gt;0.09698&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;Age&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;All&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;36.30973&lt;/TD&gt;
&lt;TD class="r data"&gt;5.534114&lt;/TD&gt;
&lt;TD class="r data"&gt;26.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;49.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;40.40483&lt;/TD&gt;
&lt;TD class="r data"&gt;6.579103&lt;/TD&gt;
&lt;TD class="r data"&gt;25.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;57.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;-4.09509&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;&amp;nbsp;&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;Region&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;36.30973&lt;/TD&gt;
&lt;TD class="r data"&gt;5.534114&lt;/TD&gt;
&lt;TD class="r data"&gt;26.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;49.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;40.40483&lt;/TD&gt;
&lt;TD class="r data"&gt;6.579103&lt;/TD&gt;
&lt;TD class="r data"&gt;25.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;57.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;-4.09509&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;&amp;nbsp;&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;Weighted&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;460.45&lt;/TD&gt;
&lt;TD class="r data"&gt;&lt;FONT size="4" color="#FF6600"&gt;&lt;STRONG&gt;38.59813&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/TD&gt;
&lt;TD class="r data"&gt;5.773228&lt;/TD&gt;
&lt;TD class="r data"&gt;26.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;49.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;489.59&lt;/TD&gt;
&lt;TD class="r data"&gt;&lt;FONT size="4" color="#800080"&gt;&lt;STRONG&gt;39.32670&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/TD&gt;
&lt;TD class="r data"&gt;6.771606&lt;/TD&gt;
&lt;TD class="r data"&gt;25.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;57.00000&lt;/TD&gt;
&lt;TD class="r data"&gt;-0.72857&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;BMI&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;All&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;24.49257&lt;/TD&gt;
&lt;TD class="r data"&gt;1.863797&lt;/TD&gt;
&lt;TD class="r data"&gt;20.33000&lt;/TD&gt;
&lt;TD class="r data"&gt;28.34000&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;23.75327&lt;/TD&gt;
&lt;TD class="r data"&gt;1.980778&lt;/TD&gt;
&lt;TD class="r data"&gt;19.22000&lt;/TD&gt;
&lt;TD class="r data"&gt;28.61000&lt;/TD&gt;
&lt;TD class="r data"&gt;0.73930&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;&amp;nbsp;&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;Region&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;24.49257&lt;/TD&gt;
&lt;TD class="r data"&gt;1.863797&lt;/TD&gt;
&lt;TD class="r data"&gt;20.33000&lt;/TD&gt;
&lt;TD class="r data"&gt;28.34000&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;23.75327&lt;/TD&gt;
&lt;TD class="r data"&gt;1.980778&lt;/TD&gt;
&lt;TD class="r data"&gt;19.22000&lt;/TD&gt;
&lt;TD class="r data"&gt;28.61000&lt;/TD&gt;
&lt;TD class="r data"&gt;0.73930&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;&amp;nbsp;&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;Weighted&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;460.45&lt;/TD&gt;
&lt;TD class="r data"&gt;24.03522&lt;/TD&gt;
&lt;TD class="r data"&gt;1.896607&lt;/TD&gt;
&lt;TD class="r data"&gt;20.33000&lt;/TD&gt;
&lt;TD class="r data"&gt;28.34000&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;489.59&lt;/TD&gt;
&lt;TD class="r data"&gt;23.95492&lt;/TD&gt;
&lt;TD class="r data"&gt;2.004019&lt;/TD&gt;
&lt;TD class="r data"&gt;19.22000&lt;/TD&gt;
&lt;TD class="r data"&gt;28.61000&lt;/TD&gt;
&lt;TD class="r data"&gt;0.08030&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;Gender&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;All&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;0.43363&lt;/TD&gt;
&lt;TD class="r data"&gt;0.495575&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;0.45845&lt;/TD&gt;
&lt;TD class="r data"&gt;0.498270&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;-0.02482&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;&amp;nbsp;&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;Region&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;0.43363&lt;/TD&gt;
&lt;TD class="r data"&gt;0.495575&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;0.45845&lt;/TD&gt;
&lt;TD class="r data"&gt;0.498270&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;-0.02482&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR&gt;
&lt;TH class="rowheader" scope="row"&gt;&amp;nbsp;&lt;/TH&gt;
&lt;TH class="rowheader" scope="row"&gt;Weighted&lt;/TH&gt;
&lt;TD class="r data"&gt;113&lt;/TD&gt;
&lt;TD class="r data"&gt;460.45&lt;/TD&gt;
&lt;TD class="r data"&gt;0.47335&lt;/TD&gt;
&lt;TD class="r data"&gt;0.499289&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;373&lt;/TD&gt;
&lt;TD class="r data"&gt;489.59&lt;/TD&gt;
&lt;TD class="r data"&gt;0.45479&lt;/TD&gt;
&lt;TD class="r data"&gt;0.497952&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;&amp;nbsp;&lt;/TD&gt;
&lt;TD class="r data"&gt;0.01856&lt;/TD&gt;
&lt;/TR&gt;
&lt;/TBODY&gt;
&lt;/TABLE&gt;
&lt;/ARTICLE&gt;
&lt;/SECTION&gt;
&lt;/SECTION&gt;
&lt;SECTION data-name="Means" data-sec-type="proc"&gt;&lt;HR /&gt;
&lt;DIV id="IDX2" class="proc_title_group"&gt;
&lt;P class="c proctitle"&gt;The MEANS Procedure&lt;/P&gt;
&lt;/DIV&gt;
&lt;SECTION&gt;
&lt;ARTICLE aria-label="Summary statistics"&gt;
&lt;P class="c byline"&gt;Drug=Drug_A&lt;/P&gt;
&lt;TABLE class="table" aria-label="Summary statistics"&gt;&lt;CAPTION aria-label="Summary statistics"&gt;&amp;nbsp;&lt;/CAPTION&gt;&lt;COLGROUP&gt;&lt;COL /&gt;&lt;/COLGROUP&gt;&lt;COLGROUP&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;/COLGROUP&gt;
&lt;THEAD&gt;
&lt;TR&gt;
&lt;TH class="b header" scope="col"&gt;Variable&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;N&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Mean&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Sum&lt;/TH&gt;
&lt;/TR&gt;
&lt;/THEAD&gt;
&lt;TBODY&gt;
&lt;TR&gt;
&lt;TH class="data"&gt;
&lt;DIV class="stacked-cell"&gt;
&lt;DIV&gt;Age&lt;/DIV&gt;
&lt;DIV&gt;BMI&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/TH&gt;
&lt;TD class="r data"&gt;
&lt;DIV class="stacked-cell"&gt;
&lt;DIV class="r"&gt;373&lt;/DIV&gt;
&lt;DIV class="r"&gt;373&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/TD&gt;
&lt;TD class="r data"&gt;
&lt;DIV class="stacked-cell"&gt;
&lt;DIV class="r"&gt;&lt;FONT size="4" color="#800080"&gt;&lt;STRONG&gt;39.3266975&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/DIV&gt;
&lt;DIV class="r"&gt;23.9549166&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/TD&gt;
&lt;TD class="r data"&gt;
&lt;DIV class="stacked-cell"&gt;
&lt;DIV class="r"&gt;19253.88&lt;/DIV&gt;
&lt;DIV class="r"&gt;11728.04&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/TD&gt;
&lt;/TR&gt;
&lt;/TBODY&gt;
&lt;/TABLE&gt;
&lt;/ARTICLE&gt;
&lt;/SECTION&gt;
&lt;SECTION id="IDX3"&gt;
&lt;ARTICLE aria-label="Summary statistics"&gt;
&lt;P class="c byline"&gt;Drug=Drug_X&lt;/P&gt;
&lt;TABLE class="table" aria-label="Summary statistics"&gt;&lt;CAPTION aria-label="Summary statistics"&gt;&amp;nbsp;&lt;/CAPTION&gt;&lt;COLGROUP&gt;&lt;COL /&gt;&lt;/COLGROUP&gt;&lt;COLGROUP&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;COL /&gt;&lt;/COLGROUP&gt;
&lt;THEAD&gt;
&lt;TR&gt;
&lt;TH class="b header" scope="col"&gt;Variable&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;N&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Mean&lt;/TH&gt;
&lt;TH class="r b header" scope="col"&gt;Sum&lt;/TH&gt;
&lt;/TR&gt;
&lt;/THEAD&gt;
&lt;TBODY&gt;
&lt;TR&gt;
&lt;TH class="data"&gt;
&lt;DIV class="stacked-cell"&gt;
&lt;DIV&gt;Age&lt;/DIV&gt;
&lt;DIV&gt;BMI&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/TH&gt;
&lt;TD class="r data"&gt;
&lt;DIV class="stacked-cell"&gt;
&lt;DIV class="r"&gt;113&lt;/DIV&gt;
&lt;DIV class="r"&gt;113&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/TD&gt;
&lt;TD class="r data"&gt;
&lt;DIV class="stacked-cell"&gt;
&lt;DIV class="r"&gt;&lt;FONT size="4" color="#FF6600"&gt;&lt;STRONG&gt;38.5981316&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/DIV&gt;
&lt;DIV class="r"&gt;24.0352189&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/TD&gt;
&lt;TD class="r data"&gt;
&lt;DIV class="stacked-cell"&gt;
&lt;DIV class="r"&gt;17772.51&lt;/DIV&gt;
&lt;DIV class="r"&gt;11067.02&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/TD&gt;
&lt;/TR&gt;
&lt;/TBODY&gt;
&lt;/TABLE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Honestly, I don't know what that first table is reporting, at least without some more research but it seems to me the weights are accurately reported.&lt;/P&gt;
&lt;/ARTICLE&gt;
&lt;/SECTION&gt;
&lt;/SECTION&gt;</description>
      <pubDate>Wed, 31 Jul 2019 00:13:59 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/577929#M28386</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2019-07-31T00:13:59Z</dc:date>
    </item>
    <item>
      <title>Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/578148#M28393</link>
      <description>&lt;P&gt;Thank you Reeza!&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I guess my question is not just for PROC PSMATCH, but about "weighted mean" in general, including PROC MEANS.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Do we calculate the weighted mean of X when Weight = Y by calculating the mean of (X1*Y1, ... Xn*Yn)?&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;</description>
      <pubDate>Wed, 31 Jul 2019 17:15:42 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/578148#M28393</guid>
      <dc:creator>withyin</dc:creator>
      <dc:date>2019-07-31T17:15:42Z</dc:date>
    </item>
    <item>
      <title>Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/578160#M28394</link>
      <description>Take a look at the code, you don't try to manually account for it, use the WEIGHT statement and specify that the Y value is your weight. This works for means, but if you're using survey weights you may want to use PROC SURVEYMEANS.</description>
      <pubDate>Wed, 31 Jul 2019 17:54:55 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/578160#M28394</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2019-07-31T17:54:55Z</dc:date>
    </item>
    <item>
      <title>Re: PSMATCH: How did SAS calculate the weighted means in Example 98.1?  see link in the text</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/578172#M28396</link>
      <description>&lt;P&gt;Thanks.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 31 Jul 2019 18:30:51 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PSMATCH-How-did-SAS-calculate-the-weighted-means-in-Example-98-1/m-p/578172#M28396</guid>
      <dc:creator>withyin</dc:creator>
      <dc:date>2019-07-31T18:30:51Z</dc:date>
    </item>
  </channel>
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