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Adjusted empirical likelihood estimation of the youden index and associated threshold for the bigamma model

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  • Letón, Emilio
  • Molanes, Elisa M.

Abstract

The Youden index is a widely used measure in the framework of medical diagnostic, where the effectiveness of a biomarker (screening marker or predictor) for classifying a disease status is studied. When the biomarker is continuous, it is important to determine the threshold or cut-off point to be used in practice for the discrimination between diseased and healthy populations. We introduce a new method based on adjusted empirical likelihood for quantiles aimed to estimate the Youden index and its associated threshold. We also include bootstrap based confidence intervals for both of them. In the simulation study, we compare this method with a recent approach based on the delta method under the bigamma scenario. Finally, a real example of prostatic cancer, well known in the literature, is analyzed to provide the reader with a better understanding of the new method

Suggested Citation

  • Letón, Emilio & Molanes, Elisa M., 2009. "Adjusted empirical likelihood estimation of the youden index and associated threshold for the bigamma model," DES - Working Papers. Statistics and Econometrics. WS ws091907, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Handle: RePEc:cte:wsrepe:ws091907
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    References listed on IDEAS

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    1. Elisa M. Molanes Lopez & Ingrid Van Keilegom & Noël Veraverbeke, 2009. "Empirical Likelihood for Non‐Smooth Criterion Functions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 413-432, September.
    2. Chen, Jian & Peng, Liang & Zhao, Yichuan, 2009. "Empirical likelihood based confidence intervals for copulas," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 137-151, January.
    3. Margaret Sullivan Pepe & Tianxi Cai, 2004. "The Analysis of Placement Values for Evaluating Discriminatory Measures," Biometrics, The International Biometric Society, vol. 60(2), pages 528-535, June.
    4. Wang Zhou & Bing-Yi Jing, 2003. "Adjusted empirical likelihood method for quantiles," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(4), pages 689-703, December.
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