Python, Statistics, Educational Measurement: Cohens kappa interrater agreement coefficient
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Cohen's kappa coefficient is a measure of interrater agreement for qualitative or categorical variables. It is computed normally only for two raters or judges . Input data is usually a 2 by 2 table. Consider the following:
| Yes | No | |
|---|---|---|
| Yes | a | b |
| No | c | d |
and a specific example(from en.wikipedial):
| 20 | 5 |
| 10 | 15 |
The following Python program computes Cohen's kappa
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | def kappa(a,b,c,d): tot = a + b + c + d Pa = float(a + d)/tot PA1 = float(a + b)/tot PA2 = 1.0- PA1 PB1 = float(a + c) /tot PB2 = 1.0 -PB1 Pe = PA1 *PB1 + PA2*PB2 print Pa, PA1, PB1, PA2, PB2 return (Pa -Pe)/ (1.0 -Pe) def Test(): a = 20 b = 5 c = 10 d = 15 print "kappa(20,5,10,15)=", kappa(a,b,c,d) if __name__ == "__main__": Test() |
When the above program runs it outputs 0.4 as it should.
A multi rater version of the Cohen's kappa is currently being worked on.
See Wikipedia for more details.
