The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Autor Ross L. Prentice, Shanshan Zhaoen Limba Engleză Hardback – 16 mai 2019
Much of the literature on the analysis of censored correlated failure time data uses frailty or copula models to allow for residual dependencies among failure times, given covariates. In contrast, this book provides a detailed account of recently developed methods for the simultaneous estimation of marginal single and dual outcome hazard rate regression parameters, with emphasis on multiplicative (Cox) models. Illustrations are provided of the utility of these methods using Women’s Health Initiative randomized controlled trial data of menopausal hormones and of a low-fat dietary pattern intervention. As byproducts, these methods provide flexible semiparametric estimators of pairwise bivariate survivor functions at specified covariate histories, as well as semiparametric estimators of cross ratio and concordance functions given covariates. The presentation also describes how these innovative methods may extend to handle issues of dependent censorship, missing and mismeasured covariates, and joint modeling of failure times and covariates, setting the stage for additional theoretical and applied developments. This book extends and continues the style of the classic Statistical Analysis of Failure Time Data by Kalbfleisch and Prentice.
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.
Toate formatele și edițiile | Preț | Express |
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Paperback (1) | 311.68 lei 6-8 săpt. | |
CRC Press – 18 dec 2020 | 311.68 lei 6-8 săpt. | |
Hardback (1) | 658.07 lei 6-8 săpt. | |
CRC Press – 16 mai 2019 | 658.07 lei 6-8 săpt. |
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Specificații
ISBN-13: 9781482256574
ISBN-10: 1482256576
Pagini: 240
Dimensiuni: 156 x 234 x 14 mm
Greutate: 0.5 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Monographs on Statistics and Applied Probability
ISBN-10: 1482256576
Pagini: 240
Dimensiuni: 156 x 234 x 14 mm
Greutate: 0.5 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Cuprins
Introduction to Multivariate Failure Time Data. Bivariate Survivor Function Representation and Estimation. Regression Analysis of Bivariate Failure Time Data. Transformation Models, Frailties and Copulas for Bivariate Failure Time Regression. Regression Analysis of Higher Dimensional Failure Time Data. Recurrent Events and Life History Analysis. Missing and Mismeasured Data in Multivariate Failure Time Analysis. Other Failure Time Data Analysis Topics.
Notă biografică
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.
Shanshan Zhao is a Principal Investigator at the National Institute of Environmental Health Sciences in Research Triangle Park, North Carolina.
Recenzii
"Here, Prentice (Univ. of Washington) and Zhao (National Inst. of Environmental Health Sciences) provide a systematic introduction to novel statistical methodology, using a “marginal modeling approach” relevant to a number of fields where interpretation of survival outcomes and failure over time data is required.The authors explore the entirety of each method covered, progressing from background mathematics to assumptions and caveats, and finally to interpretation. Intended for biostatistical researchers engaged in analysis of complex population data sets as encountered, for example, in randomized clinical trials, this volume may also serve as a reference for quantitative epidemiologists. Readers will need a solid understanding of statistical estimation methods and a reasonable command of calculus and probability theory. Appropriate exercises accompany each chapter, and links to software and sample data are provided (appendix B)."
~K. J. Whitehair, independent scholar, CHOICE, January 2020 Vol. 57 No. 5
Summing Up: Recommended. Graduate students, faculty and practitioners.
~K. J. Whitehair, independent scholar, CHOICE, January 2020 Vol. 57 No. 5
Summing Up: Recommended. Graduate students, faculty and practitioners.
Descriere
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 research concepts. Many of the illustrations are from population disease studies which should interest epidemiologists and population scientists.