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    <title>topic Factor Analysis N iteration in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Factor-Analysis-N-iteration/m-p/20474#M603</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;What you say "should work" does work.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc factor data=correl score NFACT=15 outstat=fact; &lt;/P&gt;&lt;P&gt;run; &lt;/P&gt;&lt;P&gt;proc score data=raw score=fact out=scores; &lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;If you use NFACT=15, the FACT data set contains scoring coefficients for the first 15 factors.&lt;/P&gt;&lt;P&gt;PROC SCORE projects the raw data onto the first 15 factors. The variables are FACTOR1-FACTOR15.&lt;/P&gt;&lt;P&gt;Those variables are the first 15 principal components: the linear combinations that best explain the variation in the data.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Mon, 05 Mar 2012 15:00:34 GMT</pubDate>
    <dc:creator>Rick_SAS</dc:creator>
    <dc:date>2012-03-05T15:00:34Z</dc:date>
    <item>
      <title>Factor Analysis N iteration</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Factor-Analysis-N-iteration/m-p/20473#M602</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Dear I have around 77 factors and I used factor analysis to reduce them. I also need to get scores for further analysis.&lt;/P&gt;&lt;P&gt;I used the following command..&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; proc factor data=correl score outstat=fact; &lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; run; &lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; proc score&amp;nbsp; data=raw score=fact out=scores; &lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;After running this command I got 31 factors, but I want to reduce between 10~15 factors.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I used N=15, NFACT=10 but both commands does not work.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Please give me Idea how I can reduce these factors more that also do not reduce the effect of Eigen value.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Will be thankful for your nice comments &amp;amp; suggestions&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 02 Mar 2012 18:52:44 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Factor-Analysis-N-iteration/m-p/20473#M602</guid>
      <dc:creator>Malik</dc:creator>
      <dc:date>2012-03-02T18:52:44Z</dc:date>
    </item>
    <item>
      <title>Factor Analysis N iteration</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Factor-Analysis-N-iteration/m-p/20474#M603</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;What you say "should work" does work.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc factor data=correl score NFACT=15 outstat=fact; &lt;/P&gt;&lt;P&gt;run; &lt;/P&gt;&lt;P&gt;proc score data=raw score=fact out=scores; &lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;If you use NFACT=15, the FACT data set contains scoring coefficients for the first 15 factors.&lt;/P&gt;&lt;P&gt;PROC SCORE projects the raw data onto the first 15 factors. The variables are FACTOR1-FACTOR15.&lt;/P&gt;&lt;P&gt;Those variables are the first 15 principal components: the linear combinations that best explain the variation in the data.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 05 Mar 2012 15:00:34 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Factor-Analysis-N-iteration/m-p/20474#M603</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2012-03-05T15:00:34Z</dc:date>
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