Computing Information Agreement

Abstract: Agreement measures are useful to both compare different evaluations of the same diagnostic outcomes and validate new rating systems or devices. Information Agreement (IA) is an information-theoretic-based agreement measure introduced to overcome all the limitations and alleged pitfalls of Cohen's Kappa. However, it is only able to deal with agreement matrices whose values are positive natural numbers. This work extends IA admitting also 0 as a possible value for the agreement matrix cells.