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Bayesian Nonparametric Nonproportional Hazards Survival Modeling

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  • Maria De Iorio
  • Wesley O. Johnson
  • Peter Müller
  • Gary L. Rosner

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  • Maria De Iorio & Wesley O. Johnson & Peter Müller & Gary L. Rosner, 2009. "Bayesian Nonparametric Nonproportional Hazards Survival Modeling," Biometrics, The International Biometric Society, vol. 65(3), pages 762-771, September.
    • Handle: RePEc:bla:biomet:v:65:y:2009:i:3:p:762-771
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2008.01166.x
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    References listed on IDEAS

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    1. De Iorio, Maria & Muller, Peter & Rosner, Gary L. & MacEachern, Steven N., 2004. "An ANOVA Model for Dependent Random Measures," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 205-215, January.
    2. Griffin, J.E. & Steel, M.F.J., 2006. "Order-Based Dependent Dirichlet Processes," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 179-194, March.
    3. David B. Dunson & Natesh Pillai & Ju‐Hyun Park, 2007. "Bayesian density regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 163-183, April.
    4. Gary L. Rosner, 2005. "Bayesian Monitoring of Clinical Trials with Failure-Time Endpoints," Biometrics, The International Biometric Society, vol. 61(1), pages 239-245, March.
    5. Alan E. Gelfand & Athanasios Kottas, 2003. "Bayesian Semiparametric Regression for Median Residual Life," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(4), pages 651-665, December.
    6. Stephen Walker & Bani K. Mallick, 1999. "A Bayesian Semiparametric Accelerated Failure Time Model," Biometrics, The International Biometric Society, vol. 55(2), pages 477-483, June.
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    Cited by:

    1. Vanda Inácio de Carvalho & Miguel de Carvalho & Adam J. Branscum, 2017. "Nonparametric Bayesian covariate‐adjusted estimation of the Youden index," Biometrics, The International Biometric Society, vol. 73(4), pages 1279-1288, December.
    2. Li, Mingyang & Meng, Hongdao & Zhang, Qingpeng, 2017. "A nonparametric Bayesian modeling approach for heterogeneous lifetime data with covariates," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 95-104.
    3. Bao, Junshu & Hanson, Timothy E., 2016. "A mean-constrained finite mixture of normals model," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 93-99.
    4. Antonio Lijoi & Bernardo Nipoti, 2014. "A Class of Hazard Rate Mixtures for Combining Survival Data From Different Experiments," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 802-814, June.
    5. Jiajia Zhang & Timothy Hanson & Haiming Zhou, 2019. "Bayes factors for choosing among six common survival models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 361-379, April.
    6. Yushu Shi & Purushottam Laud & Joan Neuner, 2021. "A dependent Dirichlet process model for survival data with competing risks," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(1), pages 156-176, January.
    7. Chenyang Zhang & Guosheng Yin, 2023. "Bayesian nonparametric analysis of restricted mean survival time," Biometrics, The International Biometric Society, vol. 79(2), pages 1383-1396, June.
    8. Piyali Basak & Antonio Linero & Debajyoti Sinha & Stuart Lipsitz, 2022. "Semiparametric analysis of clustered interval‐censored survival data using soft Bayesian additive regression trees (SBART)," Biometrics, The International Biometric Society, vol. 78(3), pages 880-893, September.
    9. Das, Priyam & Ghosal, Subhashis, 2018. "Bayesian non-parametric simultaneous quantile regression for complete and grid data," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 172-186.
    10. Kurtis Shuler & Samuel Verbanic & Irene A. Chen & Juhee Lee, 2021. "A Bayesian nonparametric analysis for zero‐inflated multivariate count data with application to microbiome study," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 961-979, August.
    11. Juhee Lee & Peter F. Thall & Bora Lim & Pavlos Msaouel, 2022. "Utility‐based Bayesian personalized treatment selection for advanced breast cancer," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1605-1622, November.
    12. Jackson Christopher H & Sharples Linda D & Thompson Simon G, 2010. "Survival Models in Health Economic Evaluations: Balancing Fit and Parsimony to Improve Prediction," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-31, October.
    13. Haiming Zhou & Timothy Hanson & Jiajia Zhang, 2017. "Generalized accelerated failure time spatial frailty model for arbitrarily censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 495-515, July.
    14. Li, Yunzhe & Lee, Juhee & Kottas, Athanasios, 2024. "Bayesian nonparametric Erlang mixture modeling for survival analysis," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    15. Andrés F. Barrientos & Alejandro Jara & Fernando A. Quintana, 2017. "Fully Nonparametric Regression for Bounded Data Using Dependent Bernstein Polynomials," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 806-825, April.
    16. Richardson, Robert & Hartman, Brian, 2018. "Bayesian nonparametric regression models for modeling and predicting healthcare claims," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 1-8.
    17. Antonio Lijoi & Bernardo Nipoti, 2013. "A class of hazard rate mixtures for combining survival data from different experiments," DEM Working Papers Series 059, University of Pavia, Department of Economics and Management.
    18. Chen, Kunzhi & Shen, Weining & Zhu, Weixuan, 2023. "Covariate dependent Beta-GOS process," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
    19. Michele Guindani & Wesley O. Johnson, 2018. "More nonparametric Bayesian inference in applications," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 239-251, June.
    20. Kassandra Fronczyk & Athanasios Kottas, 2017. "Risk Assessment for Toxicity Experiments with Discrete and Continuous Outcomes: A Bayesian Nonparametric Approach," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(4), pages 585-601, December.
    21. Im, Yunju & Tan, Aixin, 2021. "Bayesian subgroup analysis in regression using mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 162(C).

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