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A new threshold regression model for survival data with a cure fraction

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Abstract

Due to the fact that certain fraction of the population suffering a particular type of disease get cured because of advanced medical treatment and health care system, we develop a general class of models to incorporate a cure fraction by introducing the latent number N of metastatic-competent tumor cells or infected cells caused by bacteria or viral infection and the latent antibody level R of immune system. Various properties of the proposed models are carefully examined and a Markov chain Monte Carlo sampling algorithm is developed for carrying out Bayesian computation for model fitting and comparison. A real data set from a prostate cancer clinical trial is analyzed in detail to demonstrate the proposed methodology.

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Authors and Affiliations

  1. Division of Epidemiology, Statistics and Prevention Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Rockville, MD, 20852, USA

    Sungduk Kim

  2. Department of Statistics, University of Connecticut, Storrs, CT, 06269, USA

    Ming-Hui Chen & Dipak K. Dey

Authors
  1. Sungduk Kim
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  2. Ming-Hui Chen
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  3. Dipak K. Dey
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Correspondence to Ming-Hui Chen.

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Kim, S., Chen, MH. & Dey, D.K. A new threshold regression model for survival data with a cure fraction. Lifetime Data Anal 17, 101–122 (2011). https://doi.org/10.1007/s10985-010-9166-9

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  • DOI: https://doi.org/10.1007/s10985-010-9166-9

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