Measures of agreement between many raters for ordinal classifications

Kappa Test for Agreement Between Two Raters

Introduction This module computes power and sample size for the test of agreement between two raters using the kappa statistic. The power calculations are based on the results in Flack, Afifi, Lachenbruch, and Schouten (1988). Calculations are based on ratings for k categories from two raters or judges. You are able to vary category frequencies on a single run of the procedure to analyze a wide...

Modeling Agreement between Binary Classifications of Multiple Raters in R and SAS

Delta: a new measure of agreement between two raters.

The most common measure of agreement for categorical data is the coefficient kappa. However, kappa performs poorly when the marginal distributions are very asymmetric, it is not easy to interpret, and its definition is based on hypothesis of independence of the responses (which is more restrictive than the hypothesis that kappa has a value of zero). This paper defines a new measure of agreement...

Kappa Statistics for Multiple Raters Using Categorical Classifications

In order to assess the reliability of a given characterization of a subject it is often necessary to obtain multiple readings, usually but not always from different individuals or raters. The degree of agreement among the various raters gives some indication as to the consistency of the values. If agreement is high, we feel more confident the ratings reflect the actual circumstance. If agreemen...

Questionable Raters + Low Agreement + Inadequate Sampling

Several studies have made positive claims regarding the validity, reliability, and utility of the Occupational Information Network (O*NET). In this first of three studies questioning such claims, I focused on the root cause of many problems regarding O*NET: i.e., the practice of rating overly abstract and heterogeneous occupational units (OUs), collecting ratings on OUs that exhibit substantial...