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Generalized Logit-Based Proportional Hazards Models and Their Applications in Survival and Reliability Analyses

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Stochastic Reliability and Maintenance Modeling

Part of the book series: Springer Series in Reliability Engineering ((RELIABILITY,volume 9))

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Abstract

We introduce a flexible family of generalized logit-based regression models for survival and reliability analyses. We present its parametric as well as its semiparametric versions. The method of maximum likelihood and the partial likelihood approach are applied to estimate the parameters of the parametric and semiparametric models, respectively. This new family of models is illustrated with male laryngeal cancer data and compared with Cox regression.

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Acknowledgments

This work was supported by research grant MTM2009-06997 and MAEC-AECID.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada

    N. Balakrishnan

  2. Department of Statistics and Operational Research I, Faculty of Mathematics, Complutense University of Madrid, Madrid, Spain

    M. C. Pardo & M. L. Avendaño

Authors
  1. N. Balakrishnan
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  2. M. C. Pardo
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  3. M. L. Avendaño
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Corresponding author

Correspondence to N. Balakrishnan .

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Editors and Affiliations

  1. , Department of Information Engineering, Hiroshima University, Kagamiyama 1-4-1, Higashi-Hiroshima, 739-8527, Japan

    Tadashi Dohi

  2. , Dept. of Business administration, Aichi Institute of Technology, Yachigusa, Yagusa-cho 1247, Toyota, 470-0392, Japan

    Toshio Nakagawa

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Balakrishnan, N., Pardo, M.C., Avendaño, M.L. (2013). Generalized Logit-Based Proportional Hazards Models and Their Applications in Survival and Reliability Analyses. In: Dohi, T., Nakagawa, T. (eds) Stochastic Reliability and Maintenance Modeling. Springer Series in Reliability Engineering, vol 9. Springer, London. https://doi.org/10.1007/978-1-4471-4971-2_1

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  • DOI: https://doi.org/10.1007/978-1-4471-4971-2_1

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4970-5

  • Online ISBN: 978-1-4471-4971-2

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