PERCENT AGREE

PERCENT AGREE (LET)

Let Subcommand

Compute the percentage of values that agree in two response variables. This is pairwise agreement (i.e., how often does Y1(I) = Y2(I) for I = 1, ..., N).

Given two methods (or two labortories), it may sometimes be useful to know how often they reach the same conclusion.

For example, if we have two sensors that either detect or do not detect the presence of some quantity of interest, how often do the two detectors agree?

This command is typically used when there a discrete number of values for the variable. Often this will be two (e.g., Yes/No type data), but it is not restricted to two.

If you want to compare values for two response variables when the data is continuous, the YOUDEN PLOT is recommended.

LET <par> = PERCENT AGREE <y1> <y2>             <SUBSET/EXCEPT/FOR qualification>
where <y1> is the first response variable;
            <y2> is the second response variable;
            <par> is a parameter where the percent agree is saved;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.

LET A = PERCENT AGREE Y1 Y2
LET A = PERCENT AGREE Y1 Y2 SUBSET TAG > 1

Dataplot statistics can be used in a number of commands. For details, enter
HELP STATISTICS

None

None

PERCENT DISAGREE	= Compute the percentage of values that disagree in two response variables.
FALSE NEGATIVES	= Compute the proportion of false negatives.
FALSE POSITIVES	= Compute the proportion of false positives.
TRUE NEGATIVES	= Compute the proportion of true negatives.
TRUE POSITIVES	= Compute the proportion of true positives.
TEST SENSITIVITY	= Compute the test sensitivity.
TEST SPECIFICITY	= Compute the test specificity.
ODDS RATIO	= Compute the bias corrected log(odds ratio).
YOUDEN PLOT	= Generate a Youden plot.

Categorical Data Analysis

2011/7

 
.  Step 1: Read the Data
.
.          Column 1: Method 1 (low  => live cell, high => dead cell)
.          Column 2: Method 2 (high => live cell, low  => dead cell)
.
dimension 40 columns
read percmat  intensity
  7.1             39.8
  8.5             29.6
 72.7              4.2
 32.3             12.3
  5.4             21.5
 71.1              4.4
100.0             13.5
 55.0             22.4
 15.0             25.9
  8.7             38.5
  0.9             16.6
 19.0             48.5
100.0              4.3
100.0              7.9
  5.2             42.6
 21.8             47.2
 90.0              1.0
  2.0             23.5
 98.0              2.2
100.0              6.2
100.0              2.0
100.0              5.6
100.0              3.0
 30.0             14.3
100.0              1.0
end of data
.
.  Step 3: Generate fluctuation plot based on different levels of
.          the 2 methods
.
.          Use intensity levels of 5%, 10%, 15%, 20%, 25%
.          Use percent matching levels of 80%, 90%, 95%, 99.5%
.
let n = size intensity
let intcut = data 5 10 15 20 25
let nint = size intcut
let matcut = data 80 90 95 99.5
let nmat = size matcut
.
let int2 = intensity
let mat2 = percmat
let xgroup = 1 for i = 1 1 n
let ygroup = 1 for i = 1 1 n
let icnt = 0
.
loop for k = 1 1 nint
    let acut = intcut(k)
    loop for l = 1 1 nmat
        let bcut = matcut(l)
        let icnt = icnt + 1
        if icnt = 1
           let xgroupal = xgroup
           let ygroupal = ygroup
           let intcor = 0 for i = 1 1 n
           let intcor = 1 subset int2 >  acut
           let intall = intcor
           let matcor = 0 for i = 1 1 n
           let matcor = 1 subset mat2 < bcut
           let matall = matcor
        else
           let xgroup2 = k for i = 1 1 n
           extend xgroupal xgroup2
           let ygroup2 = l for i = 1 1 n
           extend ygroupal ygroup2
           let intcor = 0 for i = 1 1 n
           let intcor = 1 subset int2 >  acut
           extend intall intcor
           let matcor = 0 for i = 1 1 n
           let matcor = 1 subset mat2 < bcut
           extend matall matcor
        end of if
    end of loop
end of loop
.
label case asis
tic mark label case asis
title case asis
title offset 2
.
title Percent Agreement Between Method 1 and Method 2
y1label Method 1
x1label Method 2
tic offset units data
xlimits 1 nmat
major xtic mark number nmat
minor xtic mark number 0
xtic mark offset 0.7 0.7
x1tic mark label format alpha
x1tic mark label content 80% 90% 95% 99.5%
ylimits 1 nint
major ytic mark number nint
minor ytic mark number 0
ytic mark offset 0.7 0.7
y1tic mark label format alpha
y1tic mark label content 5% 10% 15% 20% 25%
.
let ylevel = data 60 70 80 85 90 101
.
let string color = g90 g20 green cyan blue orange red
line color ^color
region fill color ^color
region border color ^color
.
set fluctuation plot floor 0
set fluctuation plot ceiling  100
fluctuation percent agreement contour plot ...
            intall matall xgroupal ygroupal ylevel
.
box fill pattern solid
box shadow hw 0 0
.
box fill color g20
box 86 90 90 86 
move 91 87; text <= 60
.
box fill color green
box 86 86 90 82 
move 91 83; text 60 - 70
.
box fill color cyan
box 86 82 90 78 
move 91 79; text 70 - 80
.
box fill color blue
box 86 78 90 74 
move 91 75; text 80 - 85
.
box fill color orange
box 86 74 90 70 
move 91 71; text 85 - 90
.
box fill color red
box 86 70 90 66 
move 91 67; text > 90