Survival analysis arises in many fields of study including medicine, biology, engineering,
public health, epidemiology, and economics. This book provides a comprehensive treatment …

Survival analysis, the analysis of failure time data, is a rapid developing area and a number
of books on the topic have been published in last twenty-five years. However, all of these …

To date, several methods exist in the statistical literature for model assessment, which
purport themselves specifically as Bayesian predictive methods. The decision theoretic …

Sampling from the posterior distribution and computing posterior quanti ties of interest using
Markov chain Monte Carlo (MCMC) samples are two major challenges involved in advanced …

The use of Markov chain Monte Carlo (MCMC) methods for estimating hierarchical models
involves complex data structures and is often described as a revolutionary development. An …

An intermediate-level treatment of Bayesian hierarchical models and their applications, this
book demonstrates the advantages of a Bayesian approach to data sets involving inferences …

Interval censoring is encountered in many practical situations when the event of interest
cannot be observed and it is only known to have occurred within a time window. The theory …

Interval-censored failure time data arise in a number of fields and many authors have
discussed various issues related to their analysis. However, most of the existing methods …

Interval-Censored Time-to-Event Data: Methods and Applications collects the most recent
techniques, models, and computational tools for interval-censored time-to-event data. Top …

There has been increasing interest in applying Bayesian nonparametric methods in large
samples and high dimensions. As Markov chain Monte Carlo (MCMC) algorithms are often …