Read more
Zusatztext "This book gives thorough coverage and rigorous discussion of statistical methods for the analysis of multivariate failure time data. The structure of the book has been thoughtfully planned and it is carefully and clearly written - it does a nice job of clearly introducing concepts and models! as well as describing nonparametric methods of estimation. For the core theme on the analysis of multiple failure times! it explores different approaches to estimation and inference! and critiques competing methods in terms of robustness and efficiency. Authoritative coverage of additional topics including recurrent event analysis! multistate modeling! dependent censoring! and others! ensures it will serve as an excellent reference for those with interest in life history analysis. Illustrative examples given in the chapters help make the issues and approaches for dealing with them tangible! while the exercises at the end of each chapter give readers an opportunity to gauge their understanding of the material. It will therefore also serve very nicely as a basis for a second graduate course on specialized topics of life history analysis." (Richard Cook! U. of Waterloo)"Let me congratulate the authors with this impressive work?This book could be a textbook for an advanced masters or Ph.D level course for a degree in biostatistics and statistics?This book focusses on the case that we want to understand the association between covariate process and a multivariate survival outcome. It includes targeting the univariate conditional hazards as well as the multivariate hazards functions. Instead of targeting intensities that condition on the full observed history! it focusses on histories that exclude the failure time history! so that a change in the Z process represents a change in future multivariate survival experience. The book also reviews copula models! frailty models! and models of intensities of counting processes! beyond their marginal hazard modeling approach?An important strength is the illustrations with real world interesting data from the Women's Health Study. Another important strength is its overview of various competing approaches! making it comprehensive! beyond the presentation of the unique marginal modeling approach developed by the authors. (Mark van der Laan! University of California! Berkeley)"I expect this book to be highly useful to: (i) researches dealing with developing statistical multivariate survival methods; (ii) teachers of advanced survival methods for graduate classes; and (iii) Biostatistics/statistics PhD students focusing in the area of multivariate survival analysis. I believe that the book would be very useful as a reference and as a textbook. I! personally! would definitely use it for both purposes.. There is a need for a well-organized book focusing mainly on the recent developments in this research area! that are not included in older books...The manuscript is technically correct! very clearly written! and it is a pleasure reading it." (Malka Gorfine! Tel Aviv University) Informationen zum Autor Ross L. Prentice is Professor of Biostatistics at the Fred Hutchinson Cancer Research Center and University of Washington in Seattle, Washington. He is the recipient of COPSS Presidents and Fisher awards, the AACR Epidemiology/Prevention and Team Science awards, and is a member of the National Academy of Medicine. Shanshan Zhao is a Principal Investigator at the National Institute of Environmental Health Sciences in Research Triangle Park, North Carolina. Klappentext Though much has been written on multivariate failure time data analysis methods, a unified approach to this topic has yet to be communicated. This book aims to fill that gap through a novel focus on marginal hazard rates and cross ratio modeling. Readers will find the content useful for instruction, for application in collaborative research and as a source of novel re...
