Bounds on Concordance-Based Validation Statistics in Regression Models for Binary Responses

Denuit, Michel;Mesfioui, Mhamet;Trufin, Julien
(2016) , 16 pages

Files

ISBADP2016_46_denuit_BoundsonConcordance-BasedValidationStatisticsinRegressionModelsforBinaryResponses_dial.pdf
  • Open Access
  • Adobe PDF
  • 277.13 KB
Download

Details

Authors
  • Denuit, MichelUCLouvain
    Author
  • Mesfioui, Mhamet
    Author
  • Trufin, Julien
    Author
Abstract
Association measures based on concordance, such as Kendall's tau, Somers' delta or Goodman and Kruskal's gamma are often used to measure explained variations in regression models for binary outcomes. As responses only assume values in {0,1}, these association measures are constrained, which makes their interpretation more dificult as a relatively small value may in fact strongly support the fitted model. In this paper, we derive the set of attainable values for concordance-based association measures in this setting so that the closeness to the best-possible fit can be properly assessed.
Affiliations

Citations

  • APA
  • Chicago
  • FWB

Denuit, M., Mesfioui, M., & Trufin, J. (2016). Bounds on Concordance-Based Validation Statistics in Regression Models for Binary Responses (ISBA Discussion Paper 2016/46). https://hdl.handle.net/2078.5/180033