
TEST SPECIFICITYName:
The parameters N_{11}, N_{12}, N_{21}, and N_{22} denote the counts for each category. Success and failure can denote any binary response. Dataplot expects "success" to be coded as "1" and "failure" to be coded as "0". Some typical examples would be:
In these examples, the "ground truth" is typically given as variable 1 while some estimator of the ground truth is given as variable 2. The test specificity is then N_{22}/(N_{21}+N_{22}). That is, the test specificity is the probability that variable 2 is a failure given that variable 1 is a failure. In the context of the first example above, the test specificity is the probability that the test does not detect the disease given that the disease is not present.
<SUBSET/EXCEPT/FOR qualification> where <y1> is the first response variable; <y2> is the second response variable; <par> is a parameter where the computed test specificity is stored; and where the <SUBSET/EXCEPT/FOR qualification> is optional.
LET A = TEST SPECIFICITY Y1 Y2 SUBSET TAG > 2
let n = 1 . let p = 0.2 let y1 = binomial rand numb for i = 1 1 100 let p = 0.1 let y2 = binomial rand numb for i = 1 1 100 . let p = 0.4 let y1 = binomial rand numb for i = 101 1 200 let p = 0.08 let y2 = binomial rand numb for i = 101 1 200 . let p = 0.15 let y1 = binomial rand numb for i = 201 1 300 let p = 0.18 let y2 = binomial rand numb for i = 201 1 300 . let p = 0.6 let y1 = binomial rand numb for i = 301 1 400 let p = 0.45 let y2 = binomial rand numb for i = 301 1 400 . let p = 0.3 let y1 = binomial rand numb for i = 401 1 500 let p = 0.1 let y2 = binomial rand numb for i = 401 1 500 . let x = sequence 1 100 1 5 . let a = test specificity y1 y2 subset x = 1 tabulate test specificity y1 y2 x . label case asis xlimits 1 5 major xtic mark number 5 minor xtic mark number 0 xtic mark offset 0.5 0.5 ytic mark offset 0.05 0.05 y1label Test Specificity x1label Group ID character x blank line blank solid . test specificity plot y1 y2 x
 
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Date created: 4/13/2007 