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  <channel>
    <title>topic Re: How does SAS construct a ROC curve in SAS Health and Life Sciences</title>
    <link>https://communities.sas.com/t5/SAS-Health-and-Life-Sciences/How-does-SAS-construct-a-ROC-curve/m-p/318242#M2099</link>
    <description>&lt;P&gt;&lt;A href="http://blogs.sas.com/content/iml/2011/07/29/computing-an-roc-curve-from-basic-principles.html" target="_blank"&gt;http://blogs.sas.com/content/iml/2011/07/29/computing-an-roc-curve-from-basic-principles.html&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="http://blogs.sas.com/content/iml/2011/06/03/a-statistical-application-of-numerical-integration-the-area-under-an-roc-curve.html" target="_blank"&gt;http://blogs.sas.com/content/iml/2011/06/03/a-statistical-application-of-numerical-integration-the-area-under-an-roc-curve.html&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I do not understand how SAS calculates predicted probabilities by .00 to .50 by 0.5. Nor do I understand what they mean in relation to the number of fractures and /or no fractures at a probability level&amp;nbsp; when printed as the ‘ctable’ or [cut off table].&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;It is not predict value, it is cutoff value.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;OL&gt;
&lt;LI&gt;The print out of the Cat data gives the probability for I assume each patient. Obs 10 for instance is given as 0.22898.&amp;nbsp; Does this mean given the cut off set at 0.300&amp;nbsp; this patient is in the positive class either as a TP or a FP.&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;it should be event=0. False Positive .&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;OL&gt;
&lt;LI&gt;I am using SAS university Edition and the code for Gplot does not run.&amp;nbsp; &amp;nbsp;I note that with PROC PLOT a curve is produced. Is this because the University Edition does not support GPLOT?&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;An alternative way is using PROC SGPLOT in UE.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Is this a correct assumption?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;5 Is it possible to obtain a histogram of the _pos_ and _neg_ cases with the probability cut off values on the x axis.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;Check URL.&lt;/P&gt;</description>
    <pubDate>Mon, 12 Dec 2016 10:57:34 GMT</pubDate>
    <dc:creator>Ksharp</dc:creator>
    <dc:date>2016-12-12T10:57:34Z</dc:date>
    <item>
      <title>How does SAS construct a ROC curve</title>
      <link>https://communities.sas.com/t5/SAS-Health-and-Life-Sciences/How-does-SAS-construct-a-ROC-curve/m-p/318203#M2098</link>
      <description>&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am requesting help in understanding ROC curves as generated by PROC LOGISTIC.&lt;/P&gt;&lt;P&gt;I am using the data in Kleinbaum DG and Klein M : Logistic Regression.&lt;/P&gt;&lt;P&gt;THE data set is Knee fracture or kneefr.&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;&lt;U&gt;The outcome variable is fracture&lt;/U&gt;&lt;/STRONG&gt;&amp;nbsp;&amp;nbsp; and is binary.&lt;/P&gt;&lt;P&gt;The data set is located&amp;nbsp; at &lt;A href="http://web1.sph.emory.edu/dkleinb/logreg3.htm#data" target="_blank"&gt;http://web1.sph.emory.edu/dkleinb/logreg3.htm#data&lt;/A&gt;&lt;/P&gt;&lt;P&gt;As kneefr.sas7bdat or kneefr,dta&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The predictor variables are:&lt;/P&gt;&lt;P&gt;FLEX &amp;nbsp;[Flex the knee]&amp;nbsp; Binary&amp;nbsp; yes, no&lt;/P&gt;&lt;P&gt;WEIGHT ability to put weight on knee [yes no]&lt;/P&gt;&lt;P&gt;AGECAT&amp;nbsp; patients age greater or less then 55years&lt;/P&gt;&lt;P&gt;HEAD&amp;nbsp;&amp;nbsp;&amp;nbsp; Injury to knee head [yes no]&lt;/P&gt;&lt;P&gt;PATELLAR injury to patellar [yes no]&lt;/P&gt;&lt;P&gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;THE CODE COPIED FROM KLEINBAUM and KLEIN&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;proc logistic data = kneefr descending;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; model fracture = Flex weight agecat head patellar /pprob = .00 to .50 by .05 ctable;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; run;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;proc logistic data = kneefr descending;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; model fracture = Flex weight agecat head patellar /outroc =cat;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; run;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Proc Print Data=CAT (obs=10);&lt;/P&gt;&lt;P&gt;run;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;SYMBOL = PLUS interpol = RC;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;/P&gt;&lt;P&gt;proc gplot data=CAT;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; plot _SENSIT_*_1MSPEC_ ;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; run;&lt;/P&gt;&lt;P&gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;&amp;nbsp;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;&amp;nbsp;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;&amp;nbsp;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;&amp;nbsp;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;MY QUESTIONS&lt;/STRONG&gt;&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;I can understand that from a logistic regression and feeding in the data for an individual patient one obtains a ln(0dd) for that patient.&amp;nbsp; From this the probability of fracture for the individual.&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;I do not understand how SAS calculates predicted probabilities by .00 to .50 by 0.5. Nor do I understand what they mean in relation to the number of fractures and /or no fractures at a probability level&amp;nbsp; when printed as the ‘ctable’ or [cut off table].&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;The print out of the Cat data gives the probability for I assume each patient. Obs 10 for instance is given as 0.22898.&amp;nbsp; Does this mean given the cut off set at 0.300&amp;nbsp; this patient is in the positive class either as a TP or a FP.&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;I am using SAS university Edition and the code for Gplot does not run.&amp;nbsp; &amp;nbsp;I note that with PROC PLOT a curve is produced. Is this because the University Edition does not support GPLOT?&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Is this a correct assumption?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;5 Is it possible to obtain a histogram of the _pos_ and _neg_ cases with the probability cut off values on the x axis.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I thank you in advance for any assistance.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 12 Dec 2016 05:25:21 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Health-and-Life-Sciences/How-does-SAS-construct-a-ROC-curve/m-p/318203#M2098</guid>
      <dc:creator>isurveyor</dc:creator>
      <dc:date>2016-12-12T05:25:21Z</dc:date>
    </item>
    <item>
      <title>Re: How does SAS construct a ROC curve</title>
      <link>https://communities.sas.com/t5/SAS-Health-and-Life-Sciences/How-does-SAS-construct-a-ROC-curve/m-p/318242#M2099</link>
      <description>&lt;P&gt;&lt;A href="http://blogs.sas.com/content/iml/2011/07/29/computing-an-roc-curve-from-basic-principles.html" target="_blank"&gt;http://blogs.sas.com/content/iml/2011/07/29/computing-an-roc-curve-from-basic-principles.html&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="http://blogs.sas.com/content/iml/2011/06/03/a-statistical-application-of-numerical-integration-the-area-under-an-roc-curve.html" target="_blank"&gt;http://blogs.sas.com/content/iml/2011/06/03/a-statistical-application-of-numerical-integration-the-area-under-an-roc-curve.html&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I do not understand how SAS calculates predicted probabilities by .00 to .50 by 0.5. Nor do I understand what they mean in relation to the number of fractures and /or no fractures at a probability level&amp;nbsp; when printed as the ‘ctable’ or [cut off table].&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;It is not predict value, it is cutoff value.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;OL&gt;
&lt;LI&gt;The print out of the Cat data gives the probability for I assume each patient. Obs 10 for instance is given as 0.22898.&amp;nbsp; Does this mean given the cut off set at 0.300&amp;nbsp; this patient is in the positive class either as a TP or a FP.&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;it should be event=0. False Positive .&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;OL&gt;
&lt;LI&gt;I am using SAS university Edition and the code for Gplot does not run.&amp;nbsp; &amp;nbsp;I note that with PROC PLOT a curve is produced. Is this because the University Edition does not support GPLOT?&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;An alternative way is using PROC SGPLOT in UE.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Is this a correct assumption?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;5 Is it possible to obtain a histogram of the _pos_ and _neg_ cases with the probability cut off values on the x axis.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;Check URL.&lt;/P&gt;</description>
      <pubDate>Mon, 12 Dec 2016 10:57:34 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Health-and-Life-Sciences/How-does-SAS-construct-a-ROC-curve/m-p/318242#M2099</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2016-12-12T10:57:34Z</dc:date>
    </item>
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