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Kappa Coefficient Interpretation Value of kLevel of agreement% of data that are reliable0.40 - 0.59Weak15 - 35%0.60 - 0.79Moderate35 - 63%0.80 - 0.90Strong64 - 81%Above 0.90Almost Perfect82 - 100%2 more rows
Kappa compares the probability of agreement to that expected if the ratings are independent. The values of range lie in [ 1, 1] with 1 presenting complete agreement and 0 meaning no agreement or independence. A negative statistic implies that the agreement is worse than random.
The kappa statistic is used to control only those instances that may have been correctly classified by chance. This can be calculated using both the observed (total) accuracy and the random accuracy. Kappa can be calculated as: Kappa = (total accuracy random accuracy) / (1- random accuracy).
7 Kappa () Cohens -coefficient134 measures the degree of agreement between a pair of variables, frequently used as a metric of interrater agreement, i.e., kappa most often deals with data that are the result of a judgment, not a measurement.
The formula for Cohens kappa is the probability of agreement minus the probability of random agreement, divided by one minus the probability of random agreement.
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Note: Percent agreement can be calculated as (a+d)/(a+b+c+d) x 100 and is called po (or proportion of agreement observed). A. po or % agreement for Group 1 = (1 + 89)/(1+1+7+89) x 100=91.8%; This means that the tests agreed in 91.8% of the screenings.
Kappa is regarded as a measure of chance-adjusted agreement, calculated as pobspexp1pexp where pobs=ki=1pii and pexp=ki=1pi+p+i (pi+ and p+i are the marginal totals). Essentially, it is a measure of the agreement that is greater than expected by chance.
For the Figure 3 data, Kappa =. 85 with a 95% Confidence Interval is calculated as follows: 0.85 - 1.96 x 0.037 to 0.85 + 1.96 x 0.037, which calculates to an interval of 0.77748 to 0.92252 which rounds to a confidence interval of 0.78 to 0.92.

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