data FatComp1;
input Test Response Count;
datalines;
0 0 17
0 1 21
1 0 3
1 1 39
;
proc sort data=FatComp1;
by descending Test descending Response;
run;
proc freq data=FatComp1 order=data;
weight Count;
tables Test*Response;
run;
title 'Positive predictive value';
proc freq data=FatComp1;
where Test=1;
weight Count;
tables Response / binomial( CL = CLOPPERPEARSON WILSON level="1");
exact binomial;
run;
title 'Negative predictive value';
proc freq data=FatComp1;
where Test=0;
weight Count;
tables Response / binomial( CL = CLOPPERPEARSON WILSON level="0");
exact binomial;
run;
Hi,
Can anyone help?
In the example above I calculated the Negative predictive value (NPV) and Positive predictive value (PPV) . Now I need to know how to calculate the adjusted NPV and PPV with a prevelence of 6% with their 95% CI.
Many thanks
NPV and PPV are sensitive to prevalence, whereas likelihood ratios are not. Instead of dramatically reducing your prevalence from 75% to 6%, why not calculate the likelihood ratios as demonstrated on this page:
http://support.sas.com/kb/24/170.html
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