The Statistical Analysis Of Multivariate Failure Time Data
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The Statistical Analysis Of Multivariate Failure Time Data
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Author : Ross L. Prentice
language : en
Publisher: CRC Press
Release Date : 2019-05-14
The Statistical Analysis Of Multivariate Failure Time Data written by Ross L. Prentice and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-14 with Mathematics categories.
The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the analysis of correlated failure times. The focus is on the use of marginal single and marginal double failure hazard rate estimators for the extraction of regression information. For example, in a context of randomized trial or cohort studies, the results go beyond that obtained by analyzing each failure time outcome in a univariate fashion. The book is addressed to researchers, practitioners, and graduate students, and can be used as a reference or as a graduate course text. 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.
The Statistical Analysis Of Failure Time Data
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Author : John D. Kalbfleisch
language : en
Publisher: John Wiley & Sons
Release Date : 2011-01-25
The Statistical Analysis Of Failure Time Data written by John D. Kalbfleisch and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-25 with Mathematics categories.
Contains additional discussion and examples on left truncationas well as material on more general censoring and truncationpatterns. Introduces the martingale and counting process formulation swillbe in a new chapter. Develops multivariate failure time data in a separate chapterand extends the material on Markov and semi Markovformulations. Presents new examples and applications of data analysis.
The Statistical Analysis Of Failure Time Data
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Author : J. D. Kalbfleisch
language : en
Publisher:
Release Date : 1984
The Statistical Analysis Of Failure Time Data written by J. D. Kalbfleisch and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with categories.
Linear Regression Analysis For Multivariate Failure Time Observations
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Author : Jin-Sying Lin
language : en
Publisher:
Release Date : 1991
Linear Regression Analysis For Multivariate Failure Time Observations written by Jin-Sying Lin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with categories.
The Statistical Analysis Of Multivariate Failure Time Data
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FREE 30 Days
Author : Ross L. Prentice
language : en
Publisher: CRC Press
Release Date : 2019-05-14
The Statistical Analysis Of Multivariate Failure Time Data written by Ross L. Prentice and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-14 with Mathematics categories.
The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the analysis of correlated failure times. The focus is on the use of marginal single and marginal double failure hazard rate estimators for the extraction of regression information. For example, in a context of randomized trial or cohort studies, the results go beyond that obtained by analyzing each failure time outcome in a univariate fashion. The book is addressed to researchers, practitioners, and graduate students, and can be used as a reference or as a graduate course text. 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.
The Statistical Analysis Of Interval Censored Failure Time Data
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Author : Jianguo Sun
language : en
Publisher: Springer
Release Date : 2007-05-26
The Statistical Analysis Of Interval Censored Failure Time Data written by Jianguo Sun and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-26 with Mathematics categories.
This book collects and unifies statistical models and methods that have been proposed for analyzing interval-censored failure time data. It provides the first comprehensive coverage of the topic of interval-censored data and complements the books on right-censored data. The focus of the book is on nonparametric and semiparametric inferences, but it also describes parametric and imputation approaches. This book provides an up-to-date reference for people who are conducting research on the analysis of interval-censored failure time data as well as for those who need to analyze interval-censored data to answer substantive questions.
An Introduction To Multivariate Statistical Analysis
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Author : Theodore W. Anderson
language : en
Publisher:
Release Date : 1984-09-28
An Introduction To Multivariate Statistical Analysis written by Theodore W. Anderson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984-09-28 with Mathematics categories.
1. Introduction; 2. The multivariate normal distribution; 3. Estimation of the mean vector and the covariance matrix; 4. Distributions and uses of sample correlation coefficients; 5. The generalized T2-Statistic; 6. Classification of observations; 7. The distribution of the sample covariance matrix and the sample generalized variance; 8. Testing the general linear hypothesis; Multivariate analysis of variance; 9. Testing independence of sets of variates; 10. Testing hypothesis of equality of coariance matrices and equality of mean vectors and covariance matrices; 11. Principal components; 12. Canonical correlations and canonical variables; 13. The distributions of characteristic roots and vectors; 14. Factor analysis.
The Statistical Analysis Of Failure Time Data
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Author : John D. Kalbfleisch
language : en
Publisher: Wiley-Interscience
Release Date : 1980
The Statistical Analysis Of Failure Time Data written by John D. Kalbfleisch and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980 with Mathematics categories.
Failure time models; Inference in parametric models and related topics; The proportional hazards model; Likelihood construction and further results on the proportional hazards model; Inference based on ranks in the accelerated failure time model; Multivariate failure time data and competing risks; Miscellaneous topics.
An Introduction To Multivariate Statistical Analysis
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Author : Theodore Wilbur Anderson
language : en
Publisher: John Wiley & Sons
Release Date : 1958
An Introduction To Multivariate Statistical Analysis written by Theodore Wilbur Anderson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1958 with Mathematics categories.
The multivariate normal distribution; Estimation of the mean vector and the covariance matrix; The distributions and uses of sample correlation coefficients; The generalized T2 statistic; Classification of observations; The distribution of the sample covariance matrix and the sample generalized variance; Testing the general linear hypothesis; analysis of variance; Testing independence of sets of variates; Testing hypotheses of equality of covariance matrices and equality of mean vectors and covariance matrices; Principal components; Canonical correlation and canonical variables; The distribution of certain characteristic roots and vectors that do not depend on parameters; A review of some other work in multivariate analysis.
Statistical Analysis Of Panel Count Data
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Author : Jianguo Sun
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-09
Statistical Analysis Of Panel Count Data written by Jianguo Sun and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-09 with Medical categories.
Panel count data occur in studies that concern recurrent events, or event history studies, when study subjects are observed only at discrete time points. By recurrent events, we mean the event that can occur or happen multiple times or repeatedly. Examples of recurrent events include disease infections, hospitalizations in medical studies, warranty claims of automobiles or system break-downs in reliability studies. In fact, many other fields yield event history data too such as demographic studies, economic studies and social sciences. For the cases where the study subjects are observed continuously, the resulting data are usually referred to as recurrent event data. This book collects and unifies statistical models and methods that have been developed for analyzing panel count data. It provides the first comprehensive coverage of the topic. The main focus is on methodology, but for the benefit of the reader, the applications of the methods to real data are also discussed along with numerical calculations. There exists a great deal of literature on the analysis of recurrent event data. This book fills the void in the literature on the analysis of panel count data. This book provides an up-to-date reference for scientists who are conducting research on the analysis of panel count data. It will also be instructional for those who need to analyze panel count data to answer substantive research questions. In addition, it can be used as a text for a graduate course in statistics or biostatistics that assumes a basic knowledge of probability and statistics.