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    <title>topic ROBUSTREG warning message in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/ROBUSTREG-warning-message/m-p/621362#M29939</link>
    <description>&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&amp;nbsp; &amp;nbsp;I would really appreciate it if someone could explain these two warnings for my robust regression analysis. I want to make sure if the output is valid.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Summary: My predictors are highly right skewed, and linear regression of the raw data showed normally distributed residuals, but a large number of outliers and leverage points. Therefore, I decided to carry out robust regression. Below is my SAS log from robust regression:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;2188 ods graphics on;&lt;BR /&gt;2189 proc robustreg data = new.cov_psmd_models1 PLOTS=all method=MM;&lt;BR /&gt;2190 class GENDER51 ELEVEL01 ;&lt;BR /&gt;2191 model WFT = msmd GENDER51 ELEVEL01 V5AGE51 / diagnostics leverage;&lt;BR /&gt;2192 output out= new.model3_outputROBUSTMM;&lt;BR /&gt;2193 title "MODEL3";&lt;BR /&gt;2194 run;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;WARNING: The design matrix is singular. Some regressors are dropped from the matrix. LEVERAGE is&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;being computed on the reduced design matrix.&lt;/STRONG&gt;&lt;BR /&gt;NOTE: The initial LTS estimator has been successfully computed.&lt;BR /&gt;NOTE: Algorithm converged for the MM estimates.&lt;BR /&gt;&lt;STRONG&gt;WARNING: The reweighted scatter matrix is singular. Projected robust distances and projected&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;Mahalanobis distances are computed.&lt;/STRONG&gt;&lt;BR /&gt;NOTE: The projected MCD estimators for covariates have been successfully computed.&lt;BR /&gt;NOTE: The initial LTS estimator has been successfully computed.&lt;BR /&gt;NOTE: Algorithm converged for the location-scale MM estimates.&lt;BR /&gt;NOTE: The data set NEW.MODEL3_OUTPUTROBUSTMM has 200 observations and 13 variables.&lt;BR /&gt;NOTE: PROCEDURE ROBUSTREG used (Total process time):&lt;BR /&gt;real time 1.50 seconds&lt;BR /&gt;cpu time 0.93 seconds&lt;/P&gt;</description>
    <pubDate>Fri, 31 Jan 2020 03:28:56 GMT</pubDate>
    <dc:creator>Abishekaa</dc:creator>
    <dc:date>2020-01-31T03:28:56Z</dc:date>
    <item>
      <title>ROBUSTREG warning message</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/ROBUSTREG-warning-message/m-p/621362#M29939</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&amp;nbsp; &amp;nbsp;I would really appreciate it if someone could explain these two warnings for my robust regression analysis. I want to make sure if the output is valid.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Summary: My predictors are highly right skewed, and linear regression of the raw data showed normally distributed residuals, but a large number of outliers and leverage points. Therefore, I decided to carry out robust regression. Below is my SAS log from robust regression:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;2188 ods graphics on;&lt;BR /&gt;2189 proc robustreg data = new.cov_psmd_models1 PLOTS=all method=MM;&lt;BR /&gt;2190 class GENDER51 ELEVEL01 ;&lt;BR /&gt;2191 model WFT = msmd GENDER51 ELEVEL01 V5AGE51 / diagnostics leverage;&lt;BR /&gt;2192 output out= new.model3_outputROBUSTMM;&lt;BR /&gt;2193 title "MODEL3";&lt;BR /&gt;2194 run;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;WARNING: The design matrix is singular. Some regressors are dropped from the matrix. LEVERAGE is&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;being computed on the reduced design matrix.&lt;/STRONG&gt;&lt;BR /&gt;NOTE: The initial LTS estimator has been successfully computed.&lt;BR /&gt;NOTE: Algorithm converged for the MM estimates.&lt;BR /&gt;&lt;STRONG&gt;WARNING: The reweighted scatter matrix is singular. Projected robust distances and projected&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;Mahalanobis distances are computed.&lt;/STRONG&gt;&lt;BR /&gt;NOTE: The projected MCD estimators for covariates have been successfully computed.&lt;BR /&gt;NOTE: The initial LTS estimator has been successfully computed.&lt;BR /&gt;NOTE: Algorithm converged for the location-scale MM estimates.&lt;BR /&gt;NOTE: The data set NEW.MODEL3_OUTPUTROBUSTMM has 200 observations and 13 variables.&lt;BR /&gt;NOTE: PROCEDURE ROBUSTREG used (Total process time):&lt;BR /&gt;real time 1.50 seconds&lt;BR /&gt;cpu time 0.93 seconds&lt;/P&gt;</description>
      <pubDate>Fri, 31 Jan 2020 03:28:56 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/ROBUSTREG-warning-message/m-p/621362#M29939</guid>
      <dc:creator>Abishekaa</dc:creator>
      <dc:date>2020-01-31T03:28:56Z</dc:date>
    </item>
    <item>
      <title>Re: ROBUSTREG warning message</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/ROBUSTREG-warning-message/m-p/621412#M29940</link>
      <description>&lt;BLOCKQUOTE&gt;
&lt;P&gt;&lt;STRONG&gt;WARNING: The design matrix is singular. Some regressors are dropped from the matrix. LEVERAGE is&amp;nbsp;&lt;/STRONG&gt;&lt;STRONG&gt;being computed on the reduced design matrix.&lt;/STRONG&gt;&lt;/P&gt;
&lt;/BLOCKQUOTE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You have put more terms in the model to fit than the number of records in your data set. &lt;STRONG&gt;OR&lt;/STRONG&gt; Some of the terms in the model are perfect linear combinations of other terms in the mode.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Since I haven't seen your data, let me just comment that right-skewed does not imply that you need robust regression. Robust regression generally compensates for outliers, not for skew.&lt;/P&gt;</description>
      <pubDate>Fri, 31 Jan 2020 13:28:45 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/ROBUSTREG-warning-message/m-p/621412#M29940</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2020-01-31T13:28:45Z</dc:date>
    </item>
    <item>
      <title>Re: ROBUSTREG warning message</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/ROBUSTREG-warning-message/m-p/621463#M29941</link>
      <description>&lt;P&gt;Hi Paige,&lt;/P&gt;&lt;P&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;Thank you for the explanation. I did run a regular linear regression and see a lot of outliers and leverage points. That is the reason for using robust regression in my analysis.&lt;/P&gt;</description>
      <pubDate>Fri, 31 Jan 2020 16:10:34 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/ROBUSTREG-warning-message/m-p/621463#M29941</guid>
      <dc:creator>Abishekaa</dc:creator>
      <dc:date>2020-01-31T16:10:34Z</dc:date>
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