J. Cohen: Cohen. A coefficient of agreement for nominal scales. Educational and psychological measure, 20, 37-46. Many situations in the health sector rely on multiple people to collect research or clinical laboratory data. The question of consistency or consistency between data-gathering individuals arises immediately because of variability among human observers. Well-designed research studies must therefore include methods to measure the consistency between different data collectors. Study projects generally include the training of data collectors and the extent to which they record the same values for the same phenomena. Perfect match is rarely achieved and confidence in the study results depends in part on the amount of disagreements or errors introduced in the study due to inconsistencies between the data collectors. The extent of the match between the data collectors is called “the reliability of the Interrater.” Krippendorffs Alpha is a versatile statistic that evaluates the agreement between observers who categorize, evaluate or measure a certain number of objects against the values of a variable. It generalizes several specialized agreement coefficients by accepting any number of observers applicable to nominal, ordinal, interval and proportional levels of measurement, capable of processing missing and corrected data for small sample sizes. The field in which you work determines the acceptable level of agreement.
If it is a sporting competition, you can accept a 60% agreement to nominate a winner. However, if you look at the data from oncologists who choose to take a treatment, you need a much higher agreement – more than 90%. In general, more than 75% are considered acceptable in most areas. The agreement and the pre-agreement actually observed constitute a random agreement. Holle, H., Rein, R. (2013). Cohen`s kappa modified: Calculating the interrateal chord for segmentation and note. In H. Lausberg (Ed.), Understanding body movement: A guide to empirical research on nonverbal behaviour (With an introduction to the NEUROGES coding system, see 261-275). Frankfurt-on-Main: Publishing house Peter Lang. Percentage agreement calculation (fictitious data). Dijkstra, W., Taris, T.
(1995). Measure the adequacy between sequences. Sociological Methods – Research, 24, 214-231. doi:10.1177/0049124195024002004 Subsequent extensions of the approach included versions that could deal with “under-credits” and ordinal scales.  These extensions converge with the intra-class correlation family (ICC), which allows us to estimate reliability for each level of measurement, from the notion (kappa) to the ordinal (or ICC) at the interval (ICC or ordinal kappa) and the ratio (ICC).