The level of categories in the data. For example, if the appraisers use a 1–5 scale, the responses are 1–5.
Kappa is the ratio of the proportion of times that the appraisers agree (corrected for chance agreement) to the maximum proportion of times that the appraisers could agree (corrected for chance agreement).
Use kappa statistics to assess the degree of agreement of the nominal or ordinal ratings made by multiple appraisers when the appraisers evaluate the same samples.
Minitab can calculate both Fleiss's kappa and Cohen's kappa. Cohen's kappa is a popular statistic for measuring assessment agreement between 2 raters. Fleiss's kappa is a generalization of Cohen's kappa for more than 2 raters. In Attribute Agreement Analysis, Minitab calculates Fleiss's kappa by default.
The AIAG suggests that a kappa value of at least 0.75 indicates good agreement. However, larger kappa values, such as 0.90, are preferred.
When you have ordinal ratings, such as defect severity ratings on a scale of 1–5, Kendall's coefficients, which account for ordering, are usually more appropriate statistics to determine association than kappa alone.
For more information, see Kappa statistics and Kendall's coefficients.
The standard error for an estimated kappa statistic measures the precision of the estimate. The smaller the standard error, the more precise the estimate.
Z is the z-value, which is the approximate normal test statistic. Minitab uses the z-value to determine the p-value.
The p-value is a probability that measures the evidence against the null hypothesis. Lower p-values provide stronger evidence against the null hypothesis.
Minitab uses the z-value to determine the p-value.