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Bayesian Cox Models for Interval-Censored Survival Data

Zhang, Yue
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479476510362603

Abstract Details

2016, PhD, University of Cincinnati, Arts and Sciences: Mathematics (Statistics).
Interval-censored data arise when failure times cannot be observed exactly but can only be determined to lie within an interval. In this dissertation, our research interest focuses on correlated survival data occur when individuals under study are clustered or experience multiple events of interest. we developed three novel Bayesian Cox models to handle different types of correlated interval-censored survival data. For clustered data, we utilized a shared frailty factor for unobserved correlation between observations within the same cluster. For spatially correlated data, we first used frailty for within cluster correlation, and then assigned a conditional autoregressive distribution prior for frailties to model the spatial dependency between clusters. In the aforementioned two frailty models, we also considered time-varying coefficient for temporal covariate effect. For bivariate data, we applied copula model to account for the dependence between outcomes. Simulation studies and analysis of real data examples illustrate the performance and applications of the proposed methods.
Xia Wang, Ph.D. (Committee Chair)
Bin Zhang, Ph.D. (Committee Member)
Emily Kang, Ph.D. (Committee Member)
Bledar Konomi, Ph.D. (Committee Member)
Siva Sivaganesan, Ph.D. (Committee Member)
Seongho Song, Ph.D. (Committee Member)
105 p.
Statistics
Bayesian analysis; Cox model; Interval censoring

Recommended Citations

Citations

  • Zhang, Y. (2016). Bayesian Cox Models for Interval-Censored Survival Data [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479476510362603

    APA Style (7th edition)

  • Zhang, Yue. Bayesian Cox Models for Interval-Censored Survival Data. 2016. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479476510362603.

    MLA Style (8th edition)

  • Zhang, Yue. "Bayesian Cox Models for Interval-Censored Survival Data." Doctoral dissertation, University of Cincinnati, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479476510362603

    Chicago Manual of Style (17th edition)

ucin1479476510362603
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© 2016, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.