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Cox proportional hazards models with frailty for negatively correlated employment processes

Author

Listed:
  • Xu, Wenjing
  • Pan, Qing
  • Gastwirth, Joseph L.
Abstract
In promotion discrimination cases, individuals affected by discrimination may decide to retire earlier than otherwise. Two Cox proportional hazards models are used to describe the promotion process from non-retired employees and the retirement process, respectively. To account for a potential negative correlation between the two outcomes, promotion and retirement, frailty terms are introduced. Model diagnoses in the presence of unobserved frailty terms are difficult. Therefore, the robustness of the parameter estimates to the fitting of an unnecessary frailty or a frailty distribution or form different from the underlying one is examined. The data from a reverse discrimination case, Alexanderv.Milwaukee, are analyzed. The original finding of liability relying on a statistically significant coefficient for membership in the legally protected group (White-male) is shown to be robust to several choices of the frailty model. This provides further support for the court’s decision.

Suggested Citation

  • Xu, Wenjing & Pan, Qing & Gastwirth, Joseph L., 2014. "Cox proportional hazards models with frailty for negatively correlated employment processes," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 295-307.
    • Handle: RePEc:eee:csdana:v:70:y:2014:i:c:p:295-307
    DOI: 10.1016/j.csda.2013.09.027
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    References listed on IDEAS

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    1. Kim, Yongdai & Kim, Joungyoun & Jang, Woncheol, 2013. "An EM algorithm for the proportional hazards model with doubly censored data," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 41-51.
    2. J. Heckman & B. Singer, 1984. "The Identifiability of the Proportional Hazard Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 51(2), pages 231-241.
    3. Lei Liu & Robert A. Wolfe & Xuelin Huang, 2004. "Shared Frailty Models for Recurrent Events and a Terminal Event," Biometrics, The International Biometric Society, vol. 60(3), pages 747-756, September.
    4. Adelchi Azzalini & Antonella Capitanio, 2003. "Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t‐distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 367-389, May.
    5. O’Hagan, Adrian & Murphy, Thomas Brendan & Gormley, Isobel Claire, 2012. "Computational aspects of fitting mixture models via the expectation–maximization algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3843-3864.
    6. Gerda Claeskens & Rosemary Nguti & Paul Janssen, 2008. "One-sided tests in shared frailty models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(1), pages 69-82, May.
    7. Melnykov, Volodymyr & Melnykov, Igor, 2012. "Initializing the EM algorithm in Gaussian mixture models with an unknown number of components," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1381-1395.
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