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Approximate Bayesian Inference for Survival Models

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  • SARA MARTINO
  • RUPALI AKERKAR
  • HÅVARD RUE

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  • Sara Martino & Rupali Akerkar & Håvard Rue, 2011. "Approximate Bayesian Inference for Survival Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 38(3), pages 514-528, September.
    • Handle: RePEc:bla:scjsta:v:38:y:2011:i:3:p:514-528
    DOI: j.1467-9469.2010.00715.x
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    Citations

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    Cited by:

    1. Janet Niekerk & Haakon Bakka & Håvard Rue, 2023. "Stable Non-Linear Generalized Bayesian Joint Models for Survival-Longitudinal Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 102-128, February.
    2. Duncan Lee & Richard Mitchell, 2013. "Locally adaptive spatial smoothing using conditional auto-regressive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(4), pages 593-608, August.
    3. E. Lázaro & C. Armero & V. Gómez-Rubio, 2020. "Approximate Bayesian inference for mixture cure models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 750-767, September.
    4. Muff, Stefanie & Ott, Manuela & Braun, Julia & Held, Leonhard, 2017. "Bayesian two-component measurement error modelling for survival analysis using INLA—A case study on cardiovascular disease mortality in Switzerland," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 177-193.
    5. Tafese Ashine & Habte Tadesse Likassa & Ding-Geng Chen, 2024. "Estimating Time-to-Death and Determining Risk Predictors for Heart Failure Patients: Bayesian AFT Shared Frailty Models with the INLA Method," Stats, MDPI, vol. 7(3), pages 1-18, September.
    6. Alex Stringer & Patrick Brown & Jamie Stafford, 2021. "Approximate Bayesian inference for case‐crossover models," Biometrics, The International Biometric Society, vol. 77(3), pages 785-795, September.
    7. Nathan William Bean & Joseph George Ibrahim & Matthew Austin Psioda, 2023. "Bayesian design of multi‐regional clinical trials with time‐to‐event endpoints," Biometrics, The International Biometric Society, vol. 79(4), pages 3586-3598, December.
    8. Gressani, Oswaldo & Lambert, Philippe, 2016. "Fast Bayesian inference in semi-parametric P-spline cure survival models using Laplace approximations," LIDAM Discussion Papers ISBA 2016041, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Kehui Yao & Jun Zhu & Daniel J. O'Brien & Daniel Walsh, 2023. "Bayesian spatio‐temporal survival analysis for all types of censoring with application to a wildlife disease study," Environmetrics, John Wiley & Sons, Ltd., vol. 34(8), December.
    10. Tyler A. Scott & Nicola Ulibarri & Ryan P. Scott, 2020. "Stakeholder involvement in collaborative regulatory processes: Using automated coding to track attendance and actions," Regulation & Governance, John Wiley & Sons, vol. 14(2), pages 219-237, April.
    11. Gressani, Oswaldo & Lambert, Philippe, 2018. "Fast Bayesian inference using Laplace approximations in a flexible promotion time cure model based on P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 151-167.
    12. Martins, Thiago G. & Simpson, Daniel & Lindgren, Finn & Rue, Håvard, 2013. "Bayesian computing with INLA: New features," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 68-83.
    13. Van Niekerk, Janet & Krainski, Elias & Rustand, Denis & Rue, Håvard, 2023. "A new avenue for Bayesian inference with INLA," Computational Statistics & Data Analysis, Elsevier, vol. 181(C).

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