The increase in the number of codes leads to a gradually smaller increase in Kappa. If the number of codes is less than five, and especially if K-2, The lower Kappa values are acceptable, but the variability in prevalence must also be taken into account. For only two codes, The highest value of Kappa is .80 observers accurately .95, and the lowest value is the cappa .02 of observers accurately .80. To obtain the standard kappa error (SE), the following formula must be used: on the other hand, if there are more than 12 codes, the expected kappa value increment flattens. As a result, the percentage of the agreement could serve the purpose of measuring the amount of the agreement. In addition, the increment of the sensitivity performance metric apartment values also reaches the asymptote of more than 12 codes. Why not just use the percentage agreement? Kappa`s statistics do not correct the random agreement and the percentage of consent. The higher the accuracy of the observer, the better the overall agreement. The relationship between the level of compliance in each level of prevalence, with different accuracy of observation. The level of compliance depends mainly on the accuracy of the observer and the prevalence of the code. The “perfect” agreement only takes place when observers .90 and 95 are accurate, while all categories obtain a substantial and higher approval majority.
We find that it shows a greater resemblance between A and B in the second case, compared to the first. Indeed, if the percentage of agreement is the same, the percentage of agreement that would occur “by chance” is much higher in the first case (0.54 vs. 0.46). The prevalence of the code does not matter much with the increase in the code number. If the number of codes 6 is greater than or equal to 6, the variability of prevalence is not significant and the standard deviation of Kappa values obtained accurately by observers .80, 85, 90 and 85 is less than 0.01. The percent deal and Kappa have strengths and limits. Percentage chord statistics are easy to calculate and directly interpretable. Its main restriction is that it does not take into account the possibility that councillors guess on partitions. It may therefore overestimate the true agreement between the advisors.
The Kappa was designed to take into account the possibility of rates, but the assumptions it makes about the independence of advisers and other factors are not well supported, and it can therefore reduce the estimate of the agreement excessively. In addition, it cannot be interpreted directly, and it has therefore become common for researchers to accept low levels of kappa in their interrater reliability studies. The low level of reliability of the Interrater is unacceptable in the field of health or clinical research, especially when the results of studies can alter clinical practice in a way that leads to poorer patient outcomes. Perhaps the best advice for researchers is to calculate both the approval percentage and kappa. While there are probably a lot of rates between advisors, it may be helpful to use Kappa`s statistics, but if the evaluators are well trained and low rates are likely, the researcher can certainly rely on the percentage of consent to determine the reliability of the Interraters. The dissent is 14/16 or 0.875. The disagreement is due to the quantity, because the assignment is optimal. Kappa is 0.01.
The pioneer paper, introduced by Kappa as a new technique, was published in 1960 by Jacob Cohen in the journal Educational and Psychological Measurement.  As marusteri and Bacarea (9) have found, there is never 100% certainty about the results of the research, even if the statistical significance is reached.