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    <title>topic Propensity score matching in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Propensity-score-matching/m-p/44671#M1959</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;If you are interested in the analysis of observational studies,&lt;/P&gt;&lt;P&gt;I reccommend the following book. I think the chapter 3 will help you especially. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN id="btAsinTitle"&gt;Analysis of Observational Health Care Data Using SAS&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;A href="http://www.amazon.com/Analysis-Observational-Health-Care-Using/dp/1607642271"&gt;http://www.amazon.com/Analysis-Observational-Health-Care-Using/dp/1607642271&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Good luck.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Yasu&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Thu, 10 Nov 2011 04:23:33 GMT</pubDate>
    <dc:creator>Yasu</dc:creator>
    <dc:date>2011-11-10T04:23:33Z</dc:date>
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      <title>Propensity score matching</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Propensity-score-matching/m-p/44669#M1957</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Has anyone worked on Propensity score matching? ANy ideas how to go about it? I have never done that before. I use SAS.&lt;/P&gt;&lt;P&gt;Are there any macro programs available to do it?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Any help will be appreciated.&lt;/P&gt;&lt;P&gt;Thanks&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 10 Nov 2011 01:35:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Propensity-score-matching/m-p/44669#M1957</guid>
      <dc:creator>Ashwini_uci</dc:creator>
      <dc:date>2011-11-10T01:35:09Z</dc:date>
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    <item>
      <title>Re: Propensity score matching</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Propensity-score-matching/m-p/44670#M1958</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I have a simple one that I wrote a couple of years ago based on ideas in a paper by Craig Roberts and John R. Gerlach and the&lt;/P&gt;&lt;P&gt;PSMatching macro presented at SAS Global Forum 2007 by Marcelo Coca Perraillon. &lt;/P&gt;&lt;P&gt;&lt;SPAN&gt; &lt;/SPAN&gt;&lt;A class="jive-link-external-small" href="http://www2.sas.com/proceedings/forum2007/185-2007.pdf"&gt;http://www2.sas.com/proceedings/forum2007/185-2007.pdf&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;It assumes that you have already calculated a single numeric score variable that will be used to match cases to controls.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Here is the program header that describes what it can do.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;PRE __default_attr="plain" __jive_macro_name="code" class="jive_text_macro jive_macro_code"&gt;&lt;P&gt;%macro psmatch&lt;/P&gt;&lt;P&gt;/*----------------------------------------------------------------------&lt;/P&gt;&lt;P&gt;Propensity Score Matching - match treated cases to controls&lt;/P&gt;&lt;P&gt;----------------------------------------------------------------------*/&lt;/P&gt;&lt;P&gt;(treated=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Input dataset of treated cases (REQ) */&lt;/P&gt;&lt;P&gt;,control=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Input dataset of controls (REQ) */&lt;/P&gt;&lt;P&gt;,out=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Output dataset of matched id numbers (DEF=MATCH) */&lt;/P&gt;&lt;P&gt;,method=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Matching method (NN RADIUS CALIPER) (DEF=NN) */&lt;/P&gt;&lt;P&gt;,caliper=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Pscore delta (used by CALIPER and RADIUS method)*/&lt;/P&gt;&lt;P&gt;,id=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Name of ID variable (DEF=ID) */&lt;/P&gt;&lt;P&gt;,pscore=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Name of Propensity Score variable (DEF=PSCORE) */&lt;/P&gt;&lt;P&gt;,nmatch=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Number of controls to match per subject (DEF=1) */&lt;/P&gt;&lt;P&gt;,replacement=&amp;nbsp;&amp;nbsp; /* Select controls with replacement? (def=Y) */&lt;/P&gt;&lt;P&gt;,seed1=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Seed for randomizing treated case order */&lt;/P&gt;&lt;P&gt;,seed2=&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* Seed for randomizing control order */&lt;/P&gt;&lt;P&gt;);&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/*----------------------------------------------------------------------&lt;/P&gt;&lt;P&gt;Propensity Score Matching&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Match treated cases to one or more controls. This does simple distance&lt;/P&gt;&lt;P&gt;based on absolute difference between the Propensity Score of the case&lt;/P&gt;&lt;P&gt;and the potential matched control. The propensity score variable must&lt;/P&gt;&lt;P&gt;already be in the input datasets. Three methods of selecting the matches&lt;/P&gt;&lt;P&gt;are available.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt; Methods&lt;/P&gt;&lt;P&gt;&amp;nbsp; NN&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; - Nearest neighbor. Find control with closest propensity score.&lt;/P&gt;&lt;P&gt;&amp;nbsp; CALIPER - Same as NN but only consider scores within +/- &amp;amp;CALIPER&lt;/P&gt;&lt;P&gt;&amp;nbsp; RADIUS&amp;nbsp; - Match ALL controls within +/- &amp;amp;CALIPER&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Based on ideas in paper by Craig Roberts and John R. Gerlach and the&lt;/P&gt;&lt;P&gt;PSMatching macro presented at SAS Global Forum 2007 by Marcelo Coca&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Perraillon. &lt;/SPAN&gt;&lt;A class="jive-link-external-small" href="http://www2.sas.com/proceedings/forum2007/185-2007.pdf"&gt;http://www2.sas.com/proceedings/forum2007/185-2007.pdf&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Assumptions:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt; - TREATED and CONTROL input datasets use same variable names for ID&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; and&amp;nbsp; propensity score variables.&lt;/P&gt;&lt;P&gt; - The propensity score variable must be numeric.&lt;/P&gt;&lt;P&gt; - The ID values must be unique keys for their datasets.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Calls to: parmv.sas varexist.sas&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Outputs:&lt;/P&gt;&lt;P&gt;&amp;nbsp; Dataset with list of matched cases and controls. The output dataset&lt;/P&gt;&lt;P&gt;is not sorted. Unmatched treated cases are not included in the output.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp; VAR&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; Description&lt;/P&gt;&lt;P&gt;&amp;nbsp; -------- -------------------------------------------------------&lt;/P&gt;&lt;P&gt;&amp;nbsp; IDT&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; Treated case ID&lt;/P&gt;&lt;P&gt;&amp;nbsp; IDC&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; Control case ID&lt;/P&gt;&lt;P&gt;&amp;nbsp; DISTANCE Distance between the propensity scores (absolute value)&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Usage Notes:&lt;/P&gt;&lt;P&gt; - When using SAS Version 9.1 or higher will use a hash object.&lt;/P&gt;&lt;P&gt; - Creates work datasets _TREATED and _CONTROL.&lt;/P&gt;&lt;P&gt; - When NMATCH &amp;gt; 1 then also creates and deletes view _TREATV_.&lt;/P&gt;&lt;P&gt; - When METHOD=RADIUS replacement parameter does not apply. Controls&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; are selected within a treated case without replacement but are&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; available for matching to other treated cases (with replacement).&lt;/P&gt;&lt;P&gt; - Treated and Control datasets are randomly ordered so that when there&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; are multiple controls of equal distance a random one will be&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; selected.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;-----------------------------------------------------------------------&lt;/P&gt;&lt;P&gt;History: &lt;/P&gt;&lt;P&gt;02AUG2009&amp;nbsp; abernt Creation&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;----------------------------------------------------------------------*/&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;/PRE&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 10 Nov 2011 03:58:08 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Propensity-score-matching/m-p/44670#M1958</guid>
      <dc:creator>Tom</dc:creator>
      <dc:date>2011-11-10T03:58:08Z</dc:date>
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    <item>
      <title>Propensity score matching</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Propensity-score-matching/m-p/44671#M1959</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;If you are interested in the analysis of observational studies,&lt;/P&gt;&lt;P&gt;I reccommend the following book. I think the chapter 3 will help you especially. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN id="btAsinTitle"&gt;Analysis of Observational Health Care Data Using SAS&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;A href="http://www.amazon.com/Analysis-Observational-Health-Care-Using/dp/1607642271"&gt;http://www.amazon.com/Analysis-Observational-Health-Care-Using/dp/1607642271&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Good luck.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Yasu&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 10 Nov 2011 04:23:33 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Propensity-score-matching/m-p/44671#M1959</guid>
      <dc:creator>Yasu</dc:creator>
      <dc:date>2011-11-10T04:23:33Z</dc:date>
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