Ridit and exponential type scores for estimating the kappa statistic

Ayfer E. Yilmaz; Serpil Aktas

Article Details

Ridit and exponential type scores for estimating the kappa statistic

Authors:

Ayfer E. Yilmaz | Serpil Aktas

Publisher:

Kuwait University

Journal:

Kuwait Journal of Science Vol.45 Issue 1, pp.0-0

Document Type:

Article

Publication Date:

1/2018

Document Language:

English

Document ID (Org No.):

2001942895

pISSN:

2307-4116

Keywords:

Abstract:

 Cohen's kappa coefficient is a commonly used method for estimating interrater agreement for nominal and/or ordinal data; thus agreement is adjusted for that expected by chance. The weighted kappa statistic is used as an agreement index for ordinal data. The weights quantify the degree of discrepancy between the two categories. The choice of this particular set of weights affects the value of kappa. The common scores are Cicchetti-Allison and Fleiss-Cohen weights. In this article, we discuss the use of ridit type and exponential scores to compute kappa statistics in general.

Article Details

Ridit and exponential type scores for estimating the kappa statistic

Authors:

Ayfer E. Yilmaz | Serpil Aktas

Publisher:

Kuwait University

Journal:

Kuwait Journal of Science Vol.45 Issue 1, pp.0-0

Document Type:

Article

Publication Date:

1/2018

Document Language:

English

Document ID (Org No.):

2001942895

pISSN:

2307-4116

Cohen’s kappa

exponential scores

ordinal

ridit type scores

weights

Issues

Article Details

Ridit and exponential type scores for estimating the kappa statistic

Authors: Ayfer E. Yilmaz | Serpil Aktas

Publisher: Kuwait University

Journal: Kuwait Journal of Science Vol.45 Issue 1, pp.0-0

Document Type: Article

Publication Date: 1/2018

Document Language: English

Document ID (Org No.): 2001942895

pISSN: 2307-4116

Cohen’s kappa

exponential scores

ordinal

ridit type scores

weights

Issues

Authors:

Ayfer E. Yilmaz | Serpil Aktas

Publisher:

Kuwait University

Journal:

Kuwait Journal of Science Vol.45 Issue 1, pp.0-0

Document Type:

Article

Publication Date:

1/2018

Document Language:

English

Document ID (Org No.):

2001942895

pISSN:

2307-4116