Extending the DeLong algorithm for comparing areas under correlated receiver operating characteristic curves with missing data

Author:

Zou Lily1,Choi Yun‐Hee2ORCID,Guizzetti Leonardo2ORCID,Shu Di3ORCID,Zou Joshua1,Zou Guangyong24ORCID

Affiliation:

1. Department of Statistics and Actuarial Science University of Waterloo Waterloo Ontario Canada

2. Department of Epidemiology and Biostatistics Western University London Ontario Canada

3. Department of Biostatistics, Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania

4. Robarts Research Institute Schulich School of Medicine & Dentistry, University of Western Ontario London Ontario Canada

Abstract

A nonparametric method proposed by DeLong et al in 1988 for comparing areas under correlated receiver operating characteristic curves is used widely in practice. However, the DeLong method as implemented in popular software quietly deletes individuals with any missing values, yielding potentially invalid and/or inefficient results. We simplify the DeLong algorithm using ranks and extend it to accommodate missing data by using a mixed model approach for multivariate data. Simulation results demonstrate the validity and efficiency of our procedure for data missing at random. We illustrate our proposed procedure in SAS, Stata, and R using the original DeLong data.

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Wiley

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