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A Bayesian inference for the penalized spline joint models of longitudinal and time-to-event data: A prior sensitivity analysis

Author

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  • Thi Thu Pham Huong

    (Mathematical Department, An Giang University, Vietnam National University, Ho Chi Minh City, Vietnam)

  • Pham Hoa

    (Mathematical Department, An Giang University, Vietnam National University, Ho Chi Minh City, Vietnam)

  • Nur Darfiana

    (CSEM, Flinders University, Flinders at Tonley, GPO BOX 2100, Adelaide5001, South Australia, Australia)

Abstract

Bayesian approaches have been used in the literature to estimate the parameters for joint models of longitudinal and time-to-event data. The main aim of this paper is to analyze the impact of prior distributions on estimating parameters in a proposed fully Bayesian analysis setting for the penalized spline joint models. To achieve this aim, the joint posterior distribution of parameters in survival and longitudinal submodels is presented. The Markov chain Monte Carlo (MCMC) algorithm is then proposed, which consists of the Gibbs sampler (GS) and Metropolis Hastings (MH) algorithms to sample for the target conditional posterior distributions. The prior sensitivity analysis for the baseline hazard rate and association parameters is performed through simulation studies and a case study.

Suggested Citation

  • Thi Thu Pham Huong & Pham Hoa & Nur Darfiana, 2020. "A Bayesian inference for the penalized spline joint models of longitudinal and time-to-event data: A prior sensitivity analysis," Monte Carlo Methods and Applications, De Gruyter, vol. 26(1), pages 49-68, March.
    • Handle: RePEc:bpj:mcmeap:v:26:y:2020:i:1:p:49-68:n:5
    DOI: 10.1515/mcma-2020-2058
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    References listed on IDEAS

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    1. Michael J. Crowther & Keith R. Abrams & Paul C. Lambert, 2013. "Joint modeling of longitudinal and survival data," Stata Journal, StataCorp LP, vol. 13(1), pages 165-184, March.
    2. Wang Y. & Taylor J. M. G., 2001. "Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 895-905, September.
    3. Pham Thi Thu Huong & Darfiana Nur & Alan Branford, 2017. "Penalized spline joint models for longitudinal and time-to-event data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(20), pages 10294-10314, October.
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