A Coefficient of Discrimination for Use with Nominal and Ordinal Regression Models

Authors

Thomas J. Smith, Northern Illinois University
David A. Walker, Northern Illinois University
Cornelius M. McKenna, Chana

Author ORCID Identifier

Thomas Smith:https://orcid.org/0000-0003-1310-8742

Publication Title

Journal of Applied Statistics

ISSN

02664763

E-ISSN

44033

Document Type

Article

Abstract

This study introduces a coefficient of discrimination for use with nominal and ordinal regression models. Computation of the coefficient is demonstrated with data from the Pew Research Center’s 25th Anniversary of the Web Omnibus Survey pertaining to cell/home phone ownership, where the coefficient of discrimination indicates that respondent age and gender increased the probability of a correct versus incorrect classification by 13.9%. Additionally, the coefficient is compared to existing coefficients.

First Page

1

Last Page

12

Publication Date

1-1-2020

DOI

10.1080/02664763.2020.1796940

Keywords

goodness-of-fit, nominal regression, Ordinal regression

Recommended Citation

Smith, Thomas J.; Walker, David A.; and McKenna, Cornelius M., "A Coefficient of Discrimination for Use with Nominal and Ordinal Regression Models" (2020). NIU Bibliography. 404.
https://huskiecommons.lib.niu.edu/niubib/404

Department

Department of Educational Technology, Research and Assessment (ETRA)