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    <title>topic Re: PROC ROBUSTREG Error Message in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-ROBUSTREG-Error-Message/m-p/177608#M9218</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thank you very much for this clarification.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Mon, 12 Jan 2015 18:19:25 GMT</pubDate>
    <dc:creator>Cuneyt</dc:creator>
    <dc:date>2015-01-12T18:19:25Z</dc:date>
    <item>
      <title>PROC ROBUSTREG Error Message</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-ROBUSTREG-Error-Message/m-p/177606#M9216</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;&lt;SPAN style="font-size: 10pt;"&gt;I am trying to estimate a very simple model in PROC ROBUSTREG. I have 280 observations, several continuous independent variables and one categorical variable with 20 levels. PROC ROBUSTREG works when I use METHOD=M. However, when I use any other method (S or MM or TLS), I get the following error message.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;ERROR: The current S estimation failed because its resampling process can not collect sufficient computable samples.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;When I drop the categorical variable from the model, PROC ROBUSTREG works again. Does anyone know what this error message means and/or how to circumvent this error?&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Sat, 10 Jan 2015 20:21:49 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-ROBUSTREG-Error-Message/m-p/177606#M9216</guid>
      <dc:creator>Cuneyt</dc:creator>
      <dc:date>2015-01-10T20:21:49Z</dc:date>
    </item>
    <item>
      <title>Re: PROC ROBUSTREG Error Message</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-ROBUSTREG-Error-Message/m-p/177607#M9217</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;From the documentation of the METHOD= option (highlight added):&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Note&lt;/STRONG&gt;: Because the LTS and S methods use subsampling algorithms, these methods are not suitable in an analysis that uses variables that have only a few unequal values or a few unequal values within one BY group. &lt;STRONG&gt;For example, indicator variables that correspond to a classification variable often fall into this category&lt;/STRONG&gt;. The same issue also applies to the initial LTS and S estimates in the MM method. For a model that includes classification independent variables or continuous independent variables with a few unequal values, the M method is recommended. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;The circumvention is, unfortunately, to not use the subsampling methods.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 12 Jan 2015 13:33:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-ROBUSTREG-Error-Message/m-p/177607#M9217</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2015-01-12T13:33:09Z</dc:date>
    </item>
    <item>
      <title>Re: PROC ROBUSTREG Error Message</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/PROC-ROBUSTREG-Error-Message/m-p/177608#M9218</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thank you very much for this clarification.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 12 Jan 2015 18:19:25 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/PROC-ROBUSTREG-Error-Message/m-p/177608#M9218</guid>
      <dc:creator>Cuneyt</dc:creator>
      <dc:date>2015-01-12T18:19:25Z</dc:date>
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