Adjusted Negative predictive value (NPV) and Positive predictive value (PPV) with a 6% prevelence

[jeka1212]

 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  

[Norman21]

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