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Bayesian survival analysis

Survival analysis is normally carried out using parametric models, semi-parametric models, non-parametric models to estimate the survival rate in clinical research. However recently Bayesian models are also used to estimate the survival rate due to their ability to handle design and analysis issues in clinical research.

Last revised
Jun 2, 2026
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Survival analysis is normally carried out using parametric models, semi-parametric models, non-parametric models to estimate the survival rate in clinical research. However recently Bayesian models1 are also used to estimate the survival rate due to their ability to handle design and analysis issues in clinical research.2

References

References

  1. Ibrahim, Joseph G.; Chen, Ming-Hui; Sinha, Debajyoti (2001). Bayesian Survival Analysis – Springer. Springer Series in Statistics. doi:10.1007/978-1-4757-3447-8. ISBN 978-1-4419-2933-4.
  2. Sinha, Debajyoti; Dey, Dipak K. (September 1997). "Semiparametric Bayesian Analysis of Survival Data". Journal of the American Statistical Association. 92 (439): 1195–1212. doi:10.1080/01621459.1997.10474077.