# Attribute Agreement Analysis Deutsch

Fleiss`Kappa (named after Joseph L. Fleiss) is a statistical measure for assessing the reliability of compliance between a fixed number of reviewers in assigning categorical ratings to a number of papers or in the classification of articles. This contrasts with other kappas, such as Cohen`s Kappa, which only work if the concordance between no more than two evaluators or intra-counselor reliability (for an expert against himself) is evaluated. The measure calculates the degree of compliance in the classification in relation to what would be expected by chance. Statistical packages can calculate a default value (Z score) for cohens Kappa or Fleiss Kappa, which can be converted to a P value. However, even if the P reaches the statistical significance level (usually less than 0.05), this only indicates that the concordance between the evaluators is significantly better than might be expected. The p alone doesn`t tell you if the chord is good enough to have a high prediction value. An example of the use of Fleiss` Kappa could be this: Consider fourteen psychiatrists who are invited to examine ten patients. Each psychiatrist gives one out of five diagnoses to each patient. These are assembled into a matrix, and Fleiss`Kappa can be calculated from this matrix (see example below) to show the degree of concordance between psychiatrists above the level of concordance expected at random. The MiniTab documentation cited above states that the Automotive Industry Action Group (AIAG) “proposes that a Kappa value of at least 0.75 indicates a good match. However, Kappa`s largest values, such as 0.90, are preferred. The factor 1 – P e ̄ {displaystyle 1-{bar {P_ {e}} } } indicates the degree of correspondence reached by chance, and P ̄ − P e ̄ {displaystyle {bar {bar {P} -{bar {P_ {e} } indicates the degree of concordance actually achieved above chance} If the evaluators are in perfect compliance, then κ = 1 {displaystyle kappa =1~}.

If there is no match between the evaluators (except what is expected by chance), then ≤ κ 0 {displaystyle kappa leq 0}. Calculate P i {displaystyle P_ {i},}, the extent to which the evaluators of the subject i-tte agree (i.e. . Calculate the number of corresponding Rater-Rater pairs relative to the number of rater pairs: Fleiss`kappa is a generalization of Scott`s Pi statistics, a statistical indicator of inter-advisor reliability.  It is also related to Cohen Kappa`s statistics and youdens J, which may be more appropriate in some cases. . . . .