Titlebook: Bayesian Inference and Computation in Reliability and Survival Analysis; Yuhlong Lio,Ding-Geng Chen,Tzong-Ru Tsai Book 2022 The Editor(s)

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Review of Statistical Treatment for Oncology Dose-Escalation Trial with Prolonged Evaluation Window based approach including Continuous Reassessment Method (CRM) and Bayesian Logistic Regression Model (BLRM), and the toxicity interval-based algorithms such as Bayesian Optimal Interval Design (BOIN) and Toxicity Probability Interval method (TPI) and their respective variations. The focus of this ch

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Bayesian Sensitivity Analysis in Survival and Longitudinal Trials with Missing Datauch as the log-rank test and the Cox proportional hazards model assume non-informative censoring for time-to-event data, and mixed model analysis assumes missing-at-random (MAR) in longitudinal trials. Although such assumptions play a critical role in influencing the outcome of the analysis, there a

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Bayesian Analysis for Clustered Data under a Semi-Competing Risks Framework. In particular, relapse for any disease is quite common, which makes usage of appropriate models indispensable. Conventional models including the logistic regression model are not appropriate in accounting for patients’ transitions who die before experiencing a relapse within a time of interest. To

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Bayesian Inferences for Panel Count Data and Interval-Censored Data with Nonparametric Modeling of tred data are studied when the exact times of the events are of interest and these exact times are not directly observed but are only known to fall within some intervals formed by the observation times. Panel count data are under investigation when the exact times of the recurrent events are not of i

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Bayesian Approach for Interval-Censored Survival Data with Time-Varying Coefficientsdata are very common in medical and epidemiological studies. In this chapter, we discuss a Bayesian approach for correlated interval-censored data under a dynamic Cox regression model. Some methods that incorporate right censoring have been developed for time-to-event data with temporal covariate ef

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Bayesian Approach for Joint Modeling Longitudinal Data and Survival Data Simultaneously in Public Hee considered a randomized clinical trial in which both longitudinal data and survival data were collected to compare the efficacy and the safety of two antiretroviral drugs in treating patients who had failed or were intolerant of zidovudine (AZT) therapy. Using these data, we demonstrated the advan