The pioneer paper, introduced by Kappa as a new technique, was published in 1960 by Jacob Cohen in the journal Educational and Psychological Measurement. [5] k – number of codes and w i `displaystyle w_`ij`, x i j `displaystyle x_ `ij`, and m i `displaystyle m_`ij` are elements in the weighting, the observed or expected dies. If the diagonal cells contain weights of 0 and all out diagonal weights of 1, this formula produces the same Kappa value as the calculation shown above. Kappa statistics are used to assess the agreement between two or more advisors if the scale of measurement is categorical. In this brief summary, we discuss and interpret the main characteristics of kappa statistics, the impact of prevalence on Kappa statistics and their usefulness in clinical research. We also introduce weighted Kappa if the result is ordinal and intraclassical correlation to assess match in a case where the data are measured continuously. Kappa ignores the degree of divergence between observers and all differences are treated in the same way as complete disagreements. Therefore, if the categories are categorized, it is preferable to use Weighted Kappa (Cohen 1968) and assign different weights to subjects for which the raters differ, so that different levels of match can contribute to Kappa`s value. Kappa statistics are often used to test the reliability of interreters. The importance of the reliability of reference values lies in the fact that it represents the extent to which the data collected in the study are correct representations of the measured variables. The measurement of the extent to which data collectors assign the same score to the same variables is called the reliability of the interrater.

Although there were many methods for measuring the reliability of Interraters, they were traditionally measured as a percentage of agreement, calculated as the number of chord results divided by the total number of points. In 1960, Jacob Cohen criticized the use of the agreement as a percentage because of its inability to take random agreement into account. He introduced the Cohen-Kappa, which was designed to take into account the possibility that the spleens, due to uncertainty, guessed at least a few variables. Like most correlation statistics, the kappa can be between 1 and 1. While the Kappa is one of the most used statistics to test the reliability of interramas, it has limitations. Judgments about the level of Kappa that should be acceptable for health research are questioned.