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Proportional odds frailty model and stochastic comparisons

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  • Ramesh Gupta
  • Cheng Peng

Abstract

In this paper, we present some distributional properties of the survival and frailty distribution involved in the proportional odds (PO) frailty model. Stochastic orderings are studied for this proportional odds frailty model. It is showed that negative dependence arises in the PO frailty model as opposed to the proportional hazard frailty model. Copyright The Institute of Statistical Mathematics, Tokyo 2014

Suggested Citation

  • Ramesh Gupta & Cheng Peng, 2014. "Proportional odds frailty model and stochastic comparisons," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(5), pages 897-912, October.
  • Handle: RePEc:spr:aistmt:v:66:y:2014:i:5:p:897-912
    DOI: 10.1007/s10463-013-0432-y
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    References listed on IDEAS

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    1. 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.
    2. S. Kirmani & Ramesh Gupta, 2001. "On the Proportional Odds Model in Survival Analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(2), pages 203-216, June.
    3. Gupta, Ramesh C. & Peng, Cheng, 2009. "Estimating reliability in proportional odds ratio models," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1495-1510, February.
    4. Zhong Guan & Cheng Peng, 2011. "A rank-based empirical likelihood approach to two-sample proportional odds model and its goodness of fit," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 763-780.
    5. Agresti, Alan & Caffo, Brian & Ohman-Strickland, Pamela, 2004. "Examples in which misspecification of a random effects distribution reduces efficiency, and possible remedies," Computational Statistics & Data Analysis, Elsevier, vol. 47(3), pages 639-653, October.
    6. A. N. Pettitt, 1984. "Proportional Odds Models for Survival Data and Estimates Using Ranks," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 33(2), pages 169-175, June.
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