A function which performs exact rate ratio tests and
returns an object of class htest.

A function which performs exact rate ratio tests and returns an object of class htest.

An index of inter rater agreement among a set of raters
An index of inter rater agreement not affected by Kappa paradoxes

An index of inter-rater agreement among a set of raters
Daniele Giardiello, Piero Quatto and Stefano Vigliani

A Modification of Fleiss' Kappa in Case of Nominal and Ordinal
Variables
c(person("Daniele", "Giardiello", role ="cre",
email = "daniele.giardiello1@gmail.com"),
person("Piero", "Quatto", role = "aut",
email = "piero.quatto@unimib.it"),
person("Enrico", "Ripamonti", role = "aut"),
person("Stefano", "Vigliani", role = "ctb",
email="stefano.vigliani@izsler.it"))
Daniele Giardiello [cre],
Piero Quatto [aut],
Enrico Ripamonti [aut],
Stefano Vigliani [ctb]
The kappa statistic implemented by Fleiss is a very popular index for assessing the reliability of agreement among multiple observers. It is used both in the psychological and in the psychiatric field. Other fields of application are typically medicine, biology and engineering. Unfortunately,the kappa statistic may behave inconsistently in case of strong agreement between raters, since this index assumes lower values than it would have been expected. We propose a modification kappa implemented by Fleiss in case of nominal and ordinal variables. Monte Carlo simulations are used both to testing statistical hypotheses and to calculating percentile bootstrap confidence intervals based on proposed statistic in case of nominal and ordinal data.

A Modification of Fleiss' Kappa in case of Nominal and Ordinal
Variables
The kappa statistic implemented by Fleiss is a very popular index for assessing the reliability of agreement between two raters or among multiple observers. It is used both in the psychological and in the psychiatric field. Other fields of application are typically medicine, biology and engineering. Unfortunately,the kappa statistic may behave inconsistently in case of strong agreement between raters, since this index assumes lower values than it would have been expected. We propose a modification kappa implemented by Fleiss in case of nominal and ordinal variables. Monte Carlo simulations are used both to testing statistical hypotheses and to calculating percentile bootstrap confidence intervals based on proposed statistic in case of nominal and ordinal data.