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  <channel>
    <title>topic Re: How to get accuracy projection (90%) based on existing values in SAS Procedures</title>
    <link>https://communities.sas.com/t5/SAS-Procedures/How-to-get-accuracy-projection-90-based-on-existing-values/m-p/245960#M56192</link>
    <description>&lt;P&gt;Thanks for the reply. None of the studies included in 15 studies are part of 30 studies, and none from 30 studies are included in the 45, etc.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I am just reporting the accuracy trends for trainees compared to goldstandard results, so there is no specific answer to your question about what would I do if they lower accuracy...if they have lower accuaracy probaly they may need more studies to reach accurate diagnosis compared to goldstandard.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The graph was generated using SAS, so the data is imported to SAS from excel sheet for this purpose. On excel sheet for each variable I have accuracy values and its 95% CIs.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;90% accuracy is when 90% of trainees agree with goldstandard diagnosis. 2x2 table.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Hope this helps. I am also attaching my excel sheet which I imported to SAS.&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;*Graphs;
%macro import (df, outname);
proc import datafile="&amp;amp;df"
     out=&amp;amp;outname
     dbms=EXCEL replace;
     getnames=yes;
	 MIXED=NO;
     SCANTEXT=YES;
     USEDATE=YES;
     SCANTIME=YES;
run;

%mend import;
*Ventrics Start and stop dates;
%import (E:\HRM\Graphs.xlsx, Graphs);

ods listing close;
ods graphics / reset width=600px height=400px imagename='Fig 1' imagefmt=jpeg;
ods html file='Surg.html' path='E:\HRM' style=journal; 

/*ods html file='ap.html' path='C:\' style=journal; */
 proc sgplot data=graphs;
 scatter X=Studies Y=MP / yerrorlower=MP_LOW yerrorupper=MP_HIGH markerattrs=(color=blue symbol=CircleFilled size=8) name="scat" legendlabel="Motor Pattern";
 series X=Studies Y=MP /  lineattrs=(color=blue pattern=1) ;
scatter X=Studies Y=BP / yerrorlower=BP_LOW yerrorupper=BP_HIGH markerattrs=(color=red symbol=SquareFilled size=8) name="scat1" legendlabel="Body Pattern";
 series X=Studies Y=BP /  lineattrs=(color=red pattern=1) ;
scatter X=Studies Y=OutOb / yerrorlower=OutOb_LOW yerrorupper=OutOb_HIGH markerattrs=(color=green symbol=TriangleFilled size=8) name="scat2" legendlabel="Achalasia/ Outflow obstruction";
 series X=Studies Y=OutOb /  lineattrs=(color=green pattern=1) ;

 XAXIS TYPE = DISCRETE ;
 YAXIS LABEL = '% Accuracy'    VALUES = (0 TO 100 BY 10);
keylegend "scat" "scat1" "scat2"  "scat4"  / position=bottomleft
across=1 location=inside ;
 run;
ods html close;
ods listing;

ods listing close;
ods graphics / reset width=600px height=400px imagename='Fig 2' imagefmt=jpeg;
ods html file='Surg.html' path='E:\HRM' style=journal; 

/*ods html file='ap.html' path='C:\' style=journal; */
 proc sgplot data=graphs;
 scatter X=Studies Y=Mx / yerrorlower=Mx_LOW yerrorupper=Mx_HIGH markerattrs=(color=blue symbol=CircleFilled size=8) name="scat" legendlabel="Overall Management Decision";
 series X=Studies Y=Mx /  lineattrs=(color=blue pattern=1) ;
scatter X=Studies Y=MxEGJ / yerrorlower=MxEGJ_LOW yerrorupper=MxEGJ_HIGH markerattrs=(color=red symbol=SquareFilled size=8) name="scat1" legendlabel="Management: EGJ";
 series X=Studies Y=MxEGJ /  lineattrs=(color=red pattern=1) ;
scatter X=Studies Y=Fundo / yerrorlower=Fundo_LOW yerrorupper=Fundo_HIGH markerattrs=(color=green symbol=TriangleFilled size=8) name="scat2" legendlabel="Feasibility of Fundoplication";
 series X=Studies Y=Fundo /  lineattrs=(color=green pattern=1) ;

 XAXIS TYPE = DISCRETE ;
 YAXIS LABEL = '% Accuracy'    VALUES = (0 TO 100 BY 10);
keylegend "scat" "scat1" "scat2"  "scat4"  / position=bottomleft
across=1 location=inside ;
 run;
ods html close;
ods listing;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Mon, 25 Jan 2016 19:29:13 GMT</pubDate>
    <dc:creator>smunigala</dc:creator>
    <dc:date>2016-01-25T19:29:13Z</dc:date>
    <item>
      <title>How to get accuracy projection (90%) based on existing values</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/How-to-get-accuracy-projection-90-based-on-existing-values/m-p/245925#M56185</link>
      <description>&lt;P&gt;Hi group,&lt;/P&gt;
&lt;P&gt;I had generated SAS graph using existing data but I need help in getting projections/ estimations for number of studies required to touch approximately 90% accuracy. I would appreciate any help in this regard.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The data is about trainees reviewing number of studies to get maximum accuracy compared to gold standard value. The trainees reviewed 15 studies at a time, so I have data points baseline, 15 studies, 30 studies, etc. So I need to know how many studies are required to get Y-axis accuracy of 90%. I know that 90% has reached for one variable but I need to get projections for the other two and possibly indicate that trend in the graph I generated.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;TABLE border="0" cellpadding="0" cellspacing="0" width="640"&gt;&lt;COLGROUP&gt;&lt;COL style="width: 48pt;" span="10" width="64" /&gt; &lt;/COLGROUP&gt;
&lt;TBODY&gt;
&lt;TR style="height: 15.0pt;"&gt;
&lt;TD style="height: 15.0pt; width: 48pt;" height="20" width="64"&gt;Studies&lt;/TD&gt;
&lt;TD style="width: 48pt;" width="64"&gt;Mx&lt;/TD&gt;
&lt;TD style="width: 48pt;" width="64"&gt;Mx_low&lt;/TD&gt;
&lt;TD style="width: 48pt;" width="64"&gt;Mx_High&lt;/TD&gt;
&lt;TD style="width: 48pt;" width="64"&gt;MxEGJ&lt;/TD&gt;
&lt;TD style="width: 48pt;" width="64"&gt;MxEGJ_low&lt;/TD&gt;
&lt;TD style="width: 48pt;" width="64"&gt;MxEGJ_High&lt;/TD&gt;
&lt;TD style="width: 48pt;" width="64"&gt;Fundo&lt;/TD&gt;
&lt;TD style="width: 48pt;" width="64"&gt;Fundo_Low&lt;/TD&gt;
&lt;TD style="width: 48pt;" width="64"&gt;Fundo_High&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR style="height: 15.0pt;"&gt;
&lt;TD style="height: 15.0pt;" align="right" height="20"&gt;0&lt;/TD&gt;
&lt;TD align="right"&gt;63.6&lt;/TD&gt;
&lt;TD align="right"&gt;46.7&lt;/TD&gt;
&lt;TD align="right"&gt;77.9&lt;/TD&gt;
&lt;TD align="right"&gt;69.6&lt;/TD&gt;
&lt;TD align="right"&gt;65.2&lt;/TD&gt;
&lt;TD align="right"&gt;73.9&lt;/TD&gt;
&lt;TD align="right"&gt;56&lt;/TD&gt;
&lt;TD align="right"&gt;52&lt;/TD&gt;
&lt;TD align="right"&gt;66.5&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR style="height: 15.0pt;"&gt;
&lt;TD style="height: 15.0pt;" align="right" height="20"&gt;15&lt;/TD&gt;
&lt;TD align="right"&gt;66&lt;/TD&gt;
&lt;TD align="right"&gt;53&lt;/TD&gt;
&lt;TD align="right"&gt;77&lt;/TD&gt;
&lt;TD align="right"&gt;91&lt;/TD&gt;
&lt;TD align="right"&gt;70&lt;/TD&gt;
&lt;TD align="right"&gt;97&lt;/TD&gt;
&lt;TD align="right"&gt;42&lt;/TD&gt;
&lt;TD align="right"&gt;24&lt;/TD&gt;
&lt;TD align="right"&gt;57&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR style="height: 15.0pt;"&gt;
&lt;TD style="height: 15.0pt;" align="right" height="20"&gt;30&lt;/TD&gt;
&lt;TD align="right"&gt;89.5&lt;/TD&gt;
&lt;TD align="right"&gt;76&lt;/TD&gt;
&lt;TD align="right"&gt;92&lt;/TD&gt;
&lt;TD align="right"&gt;83&lt;/TD&gt;
&lt;TD align="right"&gt;58&lt;/TD&gt;
&lt;TD align="right"&gt;87&lt;/TD&gt;
&lt;TD align="right"&gt;91&lt;/TD&gt;
&lt;TD align="right"&gt;73&lt;/TD&gt;
&lt;TD align="right"&gt;95&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR style="height: 15.0pt;"&gt;
&lt;TD style="height: 15.0pt;" align="right" height="20"&gt;45&lt;/TD&gt;
&lt;TD align="right"&gt;81&lt;/TD&gt;
&lt;TD align="right"&gt;61&lt;/TD&gt;
&lt;TD align="right"&gt;92&lt;/TD&gt;
&lt;TD align="right"&gt;70.5&lt;/TD&gt;
&lt;TD align="right"&gt;44&lt;/TD&gt;
&lt;TD align="right"&gt;89.5&lt;/TD&gt;
&lt;TD align="right"&gt;90&lt;/TD&gt;
&lt;TD align="right"&gt;69.3&lt;/TD&gt;
&lt;TD align="right"&gt;98.2&lt;/TD&gt;
&lt;/TR&gt;
&lt;TR style="height: 15.0pt;"&gt;
&lt;TD style="height: 15.0pt;" align="right" height="20"&gt;60&lt;/TD&gt;
&lt;TD align="right"&gt;84.6&lt;/TD&gt;
&lt;TD align="right"&gt;62.6&lt;/TD&gt;
&lt;TD align="right"&gt;91.9&lt;/TD&gt;
&lt;TD align="right"&gt;73.3&lt;/TD&gt;
&lt;TD align="right"&gt;49.2&lt;/TD&gt;
&lt;TD align="right"&gt;80&lt;/TD&gt;
&lt;TD align="right"&gt;86.7&lt;/TD&gt;
&lt;TD align="right"&gt;69.3&lt;/TD&gt;
&lt;TD align="right"&gt;93.3&lt;/TD&gt;
&lt;/TR&gt;
&lt;/TBODY&gt;
&lt;/TABLE&gt;&lt;BR /&gt;&lt;IMG src="https://communities.sas.com/t5/image/serverpage/image-id/12230i64DC66397F7B6867/image-size/large?v=1.0&amp;amp;px=600" border="0" alt="Fig2.jpg" title="Fig2.jpg" /&gt;</description>
      <pubDate>Mon, 25 Jan 2016 17:53:13 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/How-to-get-accuracy-projection-90-based-on-existing-values/m-p/245925#M56185</guid>
      <dc:creator>smunigala</dc:creator>
      <dc:date>2016-01-25T17:53:13Z</dc:date>
    </item>
    <item>
      <title>Re: How to get accuracy projection (90%) based on existing values</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/How-to-get-accuracy-projection-90-based-on-existing-values/m-p/245948#M56189</link>
      <description>&lt;P&gt;Does your "30 studies" result include the same studies in the "15 studies" and similar for the 45 or 60?&lt;/P&gt;
&lt;P&gt;What were the rules for assigning studies to the groups?&lt;/P&gt;
&lt;P&gt;What would you do if the data presented shows that the more studies included the "lower" the accuracy?&lt;/P&gt;
&lt;P&gt;Which variable(s) are you using to determine the "accuracy"?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;From the graph presented I think we also need to ask, have you brought this data into SAS yet?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;One would also be tempted to ask how you define "90% accuracy" in terms of the basic data.&lt;/P&gt;</description>
      <pubDate>Mon, 25 Jan 2016 18:53:58 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/How-to-get-accuracy-projection-90-based-on-existing-values/m-p/245948#M56189</guid>
      <dc:creator>ballardw</dc:creator>
      <dc:date>2016-01-25T18:53:58Z</dc:date>
    </item>
    <item>
      <title>Re: How to get accuracy projection (90%) based on existing values</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/How-to-get-accuracy-projection-90-based-on-existing-values/m-p/245960#M56192</link>
      <description>&lt;P&gt;Thanks for the reply. None of the studies included in 15 studies are part of 30 studies, and none from 30 studies are included in the 45, etc.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I am just reporting the accuracy trends for trainees compared to goldstandard results, so there is no specific answer to your question about what would I do if they lower accuracy...if they have lower accuaracy probaly they may need more studies to reach accurate diagnosis compared to goldstandard.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The graph was generated using SAS, so the data is imported to SAS from excel sheet for this purpose. On excel sheet for each variable I have accuracy values and its 95% CIs.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;90% accuracy is when 90% of trainees agree with goldstandard diagnosis. 2x2 table.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Hope this helps. I am also attaching my excel sheet which I imported to SAS.&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;*Graphs;
%macro import (df, outname);
proc import datafile="&amp;amp;df"
     out=&amp;amp;outname
     dbms=EXCEL replace;
     getnames=yes;
	 MIXED=NO;
     SCANTEXT=YES;
     USEDATE=YES;
     SCANTIME=YES;
run;

%mend import;
*Ventrics Start and stop dates;
%import (E:\HRM\Graphs.xlsx, Graphs);

ods listing close;
ods graphics / reset width=600px height=400px imagename='Fig 1' imagefmt=jpeg;
ods html file='Surg.html' path='E:\HRM' style=journal; 

/*ods html file='ap.html' path='C:\' style=journal; */
 proc sgplot data=graphs;
 scatter X=Studies Y=MP / yerrorlower=MP_LOW yerrorupper=MP_HIGH markerattrs=(color=blue symbol=CircleFilled size=8) name="scat" legendlabel="Motor Pattern";
 series X=Studies Y=MP /  lineattrs=(color=blue pattern=1) ;
scatter X=Studies Y=BP / yerrorlower=BP_LOW yerrorupper=BP_HIGH markerattrs=(color=red symbol=SquareFilled size=8) name="scat1" legendlabel="Body Pattern";
 series X=Studies Y=BP /  lineattrs=(color=red pattern=1) ;
scatter X=Studies Y=OutOb / yerrorlower=OutOb_LOW yerrorupper=OutOb_HIGH markerattrs=(color=green symbol=TriangleFilled size=8) name="scat2" legendlabel="Achalasia/ Outflow obstruction";
 series X=Studies Y=OutOb /  lineattrs=(color=green pattern=1) ;

 XAXIS TYPE = DISCRETE ;
 YAXIS LABEL = '% Accuracy'    VALUES = (0 TO 100 BY 10);
keylegend "scat" "scat1" "scat2"  "scat4"  / position=bottomleft
across=1 location=inside ;
 run;
ods html close;
ods listing;

ods listing close;
ods graphics / reset width=600px height=400px imagename='Fig 2' imagefmt=jpeg;
ods html file='Surg.html' path='E:\HRM' style=journal; 

/*ods html file='ap.html' path='C:\' style=journal; */
 proc sgplot data=graphs;
 scatter X=Studies Y=Mx / yerrorlower=Mx_LOW yerrorupper=Mx_HIGH markerattrs=(color=blue symbol=CircleFilled size=8) name="scat" legendlabel="Overall Management Decision";
 series X=Studies Y=Mx /  lineattrs=(color=blue pattern=1) ;
scatter X=Studies Y=MxEGJ / yerrorlower=MxEGJ_LOW yerrorupper=MxEGJ_HIGH markerattrs=(color=red symbol=SquareFilled size=8) name="scat1" legendlabel="Management: EGJ";
 series X=Studies Y=MxEGJ /  lineattrs=(color=red pattern=1) ;
scatter X=Studies Y=Fundo / yerrorlower=Fundo_LOW yerrorupper=Fundo_HIGH markerattrs=(color=green symbol=TriangleFilled size=8) name="scat2" legendlabel="Feasibility of Fundoplication";
 series X=Studies Y=Fundo /  lineattrs=(color=green pattern=1) ;

 XAXIS TYPE = DISCRETE ;
 YAXIS LABEL = '% Accuracy'    VALUES = (0 TO 100 BY 10);
keylegend "scat" "scat1" "scat2"  "scat4"  / position=bottomleft
across=1 location=inside ;
 run;
ods html close;
ods listing;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 25 Jan 2016 19:29:13 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/How-to-get-accuracy-projection-90-based-on-existing-values/m-p/245960#M56192</guid>
      <dc:creator>smunigala</dc:creator>
      <dc:date>2016-01-25T19:29:13Z</dc:date>
    </item>
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