Cohen`s Kappa statistics (or simply Kappa) are supposed to measure the concordance between two evaluators. Kappa measures an agreement. A perfect match is when all counts fall on the main diagonal of the table and the probability of an agreement is equal to 1. I have 25 items that are rated 0-4 (from Impossible to Normal). How can I calculate the reliability of the inter-advisor between two evaluators and the intra-board reliability between two meetings for each element? If it`s a Kappa weight, how do you calculate the 95% confidence interval in Excel? How to calculate a single final score of Kappa. Tom, Cohen`s kappa compensates for the random consensus, but I don`t think it`s based on the uncertainty of the evaluators. There are other tests you can use. Z.B Gwets AC1/AC2. Charles Z 1 – α / 2 = 1.965 {displaystyle Z_ {1-alpha /2} =1.965} is the normal standard percentrtil if α = 5% {displaystyle alpha =5% and S E κ = p o ( 1 − p o) N ( 1 − p e) 2 {displaystyle SE_ {kappa } ={sqrt {{p_ {o} (1-p_ {o}} over {N (1-p_{e {2}}}} Table 3 contains a general scheme and seven specific weightings of literature. The identity weighting scheme for nominal categories was introduced in Cohen [11].

The top table in Table 2 is an example of a nominal scale. The quadratic weighting scheme for continuous ordinal categories was introduced to Cohen [8]. The square weight Kappa is the most popular version of the weighted Kappa [4, 5, 15]. The linear weighting scheme for continuous ordinal categories was introduced in Cicchetti and Allison [29] and Cicchetti [30]. The second table in Table 2 is an example of a continuous ordinal scale. The dichotomous-ordinal weighting scheme was introduced in Cicchetti [9]. The two lower tables in Table 2 are examples of dichotomous-ordinal scales. All the weighting schemes in Table 3, with the exception of the general and square symmetric schemes, are special cases of the weighted scheme with additive weights introduced in Les Warrens [31]. Note that if we assign all weights on the main diagonal to 0 and all weights outside the main diagonal to 1, we have another way to calculate the unweighted Kappa, as shown in Figure 2. Richard, I haven`t implemented a default error for weighted kappa yet.

I found the following article that might be useful to you: www.itc.nl/~rossiter/teach/R/R_ac.pdf (see page 19). Charles` special cases are determined using the specific weighting schemes in Table 3 in the general formula (2). Unweighted Kappa, linearly weighted Kappa, square weighted Kappa and Cicchettis weighted Cappa are defined as given the assumption of a multinomic sample with the total number of objects, the maximum probability estimate of the probability of the cell is given by , the observed frequency being given. Note that functions and functions are cellular probabilities. The maximum probability of (2) is obtained by replacing the cellular probabilities with [32]. The last column of Table 2 contains the weighted kappas estimates for each of the four tables. For the top table in Table 2, we have for example , and . .

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