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XLeratorDB/statistics Documentation

SQL Server Cohen's Kappa function


KAPPA_COHEN

Updated: 24 May 2013


Use the scalar function KAPPA_COHEN to calculate Cohen’s kappa (Κ) or weighted kappa as an index of inter-rater agreement between 2 raters. For weighted kappa, ratings must be ordinal. KAPPA_COHEN supports quadratic and linear weighting.
The equation for Κ is

XLeratorDB formula for KAPPA COHEN function for SQL Server
Where:
Pa is the relative observed agreement among raters
Pc is the hypothetical probability of chance agreement
Syntax
SELECT [wctStatistics].[wct].[KAPPA_COHEN](
  <@InputData_RangeQuery, nvarchar(max),>
 ,<@RV, nvarchar(4000),>
 ,<@Weighting, nvarchar(4000),>)
Arguments
@InputData_RangeQuery
a T-SQL statement, as a string, that specifies the rating 1- and rating2- values.
@RV
the value to be returned by the function. Use the following values:

'PA'
the relative observed agreement among raters
'PC'
the hypothetical probability of chance agreement
'K'
the test statistic
'P'
the p-value
'Z'
K / SE
'SE'
the standard error
'NS'
the number of subjects
'NR'
the number of ratings
 
@Weight
identifies the weighting algorithm to be used. Permitted values are un-weighted, linear, and quadratic.
Return Type
float
Remarks
·         The function is insensitive to order; it does not matter what order the ratings are passed in.
·         Ratings are passed in as pairs.
·         For more than 2 raters, consider using KAPPA_FLEISS.
·         If @Weight is NULL, then @Weight = 'U'.
·         For quadratic weighting, set @Weight = 'Q'.
·         For linear weighting, set @Weight = 'L'.
Examples
SELECT *
INTO #k
FROM (
      SELECT 1,1 UNION ALL
      SELECT 1,1 UNION ALL
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      SELECT 1,2 UNION ALL
      SELECT 1,2 UNION ALL
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      )n(r1, r2)
 
SELECT p.stat
,wct.KAPPA_COHEN('SELECT r1,r2 FROM #k', p.stat, 'U') k
FROM (           
      SELECT 'Pa' UNION ALL
      SELECT 'Pc' UNION ALL
      SELECT 'K' UNION ALL
      SELECT 'P' UNION ALL
      SELECT 'Z' UNION ALL
      SELECT 'SE' UNION ALL
      SELECT 'NS' UNION ALL
      SELECT 'NR')p(stat)
This produces the following result.


Here an example using quadratic weighting.
;with mycte(subj,rater,rating) as (
SELECT 1,'R1','c' UNION ALL   SELECT 1,'R2','d' UNION ALL
SELECT 2,'R1','c' UNION ALL   SELECT 2,'R2','a' UNION ALL
SELECT 3,'R1','c' UNION ALL   SELECT 3,'R2','a' UNION ALL
SELECT 4,'R1','c' UNION ALL   SELECT 4,'R2','c' UNION ALL
SELECT 5,'R1','c' UNION ALL   SELECT 5,'R2','b' UNION ALL
SELECT 6,'R1','b' UNION ALL   SELECT 6,'R2','b' UNION ALL
SELECT 7,'R1','c' UNION ALL   SELECT 7,'R2','a' UNION ALL
SELECT 8,'R1','d' UNION ALL   SELECT 8,'R2','c' UNION ALL
SELECT 9,'R1','b' UNION ALL   SELECT 9,'R2','a' UNION ALL
SELECT 10,'R1','b' UNION ALL SELECT 10,'R2','b' UNION ALL
SELECT 11,'R1','a' UNION ALL SELECT 11,'R2','d' UNION ALL
SELECT 12,'R1','c' UNION ALL SELECT 12,'R2','d' UNION ALL
SELECT 13,'R1','a' UNION ALL SELECT 13,'R2','d' UNION ALL
SELECT 14,'R1','b' UNION ALL SELECT 14,'R2','c' UNION ALL
SELECT 15,'R1','a' UNION ALL SELECT 15,'R2','a' UNION ALL
SELECT 16,'R1','c' UNION ALL SELECT 16,'R2','a' UNION ALL
SELECT 17,'R1','a' UNION ALL SELECT 17,'R2','c' UNION ALL
SELECT 18,'R1','b' UNION ALL SELECT 18,'R2','d' UNION ALL
SELECT 19,'R1','b' UNION ALL SELECT 19,'R2','b' UNION ALL
SELECT 20,'R1','c' UNION ALL SELECT 20,'R2','c' UNION ALL
SELECT 21,'R1','d' UNION ALL SELECT 21,'R2','d' UNION ALL
SELECT 22,'R1','b' UNION ALL SELECT 22,'R2','d' UNION ALL
SELECT 23,'R1','a' UNION ALL SELECT 23,'R2','a' UNION ALL
SELECT 24,'R1','d' UNION ALL SELECT 24,'R2','b' UNION ALL
SELECT 25,'R1','b' UNION ALL SELECT 25,'R2','b'
)
SELECT m1.rating as r1
,m2.rating as r2
INTO #c
FROM mycte m1
JOIN mycte m2
ON m1.subj = m2.subj
WHERE m1.rater = 'R1'
AND m2.rater = 'R2'
 
SELECT p.*
,wct.KAPPA_COHEN('SELECT r1,r2 FROM #C',p.stat,'Q') k
FROM (
      SELECT 'Pa' UNION ALL
      SELECT 'Pc' UNION ALL
      SELECT 'K' UNION ALL
      SELECT 'P' UNION ALL
      SELECT 'Z' UNION ALL
      SELECT 'SE' UNION ALL
      SELECT 'NS' UNION ALL
      SELECT 'NR')p(stat)
This produces the following result.

 
 


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