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Full Description
Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate data and distributions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametric methods.
There are many books covering survival analysis, but very few that cover the multivariate case in any depth. Written for a graduate-level audience in statistics/biostatistics, this book includes practical exercises and R code for the examples. The author is renowned for his clear writing style, and this book continues that trend. It is an excellent reference for graduate students and researchers looking for grounding in this burgeoning field of research.
Contents
Univariate Survival Analysis: Survival Data. Survival Distributions. Frailty Models. Parametric Methods. Discrete Time: Non- And Semi-Parametric Methods. Continuous-Time: Non- And Semi-Parametric Methods. Multivariate Survival Analysis: Multivariate Data and Distributions. Frailty and Copulas. Repeated Measure. Wear and Degradation. Competing Risks: Continuous Failure Times And Their Causes. Parametric Likelihood Inference. Latent Failure Times: Probability Distributions. Discrete Failure Times in Competing Risks. Hazard-Based Methods for Continuous Failure Times. Latent Failure Times: Identifiability Crises. Counting Processes in Survival Analysis: Some Basic Concepts. Survival Analysis. Non- And Semi-Parametric Methods.
