The Statistical Analysis Of Failure Time Data PDF Download
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Author | : John D. Kalbfleisch |
Publisher | : John Wiley & Sons |
Total Pages | : 462 |
Release | : 2011-01-25 |
Genre | : Mathematics |
ISBN | : 1118031237 |
Download The Statistical Analysis of Failure Time Data Book in PDF, ePub and Kindle
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.
Author | : J. D. Kalbfleisch |
Publisher | : |
Total Pages | : |
Release | : 1984 |
Genre | : |
ISBN | : |
Download The Statistical Analysis of Failure Time Data Book in PDF, ePub and Kindle
Author | : John D. Kalbfleisch |
Publisher | : Wiley-Interscience |
Total Pages | : 344 |
Release | : 1980 |
Genre | : Mathematics |
ISBN | : |
Download The Statistical Analysis of Failure Time Data Book in PDF, ePub and Kindle
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.
Author | : Jianguo Sun |
Publisher | : Springer |
Total Pages | : 304 |
Release | : 2007-05-26 |
Genre | : Mathematics |
ISBN | : 0387371192 |
Download The Statistical Analysis of Interval-censored Failure Time Data Book in PDF, ePub and Kindle
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.
Author | : Ross L. Prentice |
Publisher | : CRC Press |
Total Pages | : 224 |
Release | : 2019-05-14 |
Genre | : Mathematics |
ISBN | : 1482256584 |
Download The Statistical Analysis of Multivariate Failure Time Data Book in PDF, ePub and Kindle
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.
Author | : Peter J. Smith |
Publisher | : CRC Press |
Total Pages | : 258 |
Release | : 2017-07-28 |
Genre | : Mathematics |
ISBN | : 1351989677 |
Download Analysis of Failure and Survival Data Book in PDF, ePub and Kindle
Analysis of Failure and Survival Data is an essential textbook for graduate-level students of survival analysis and reliability and a valuable reference for practitioners. It focuses on the many techniques that appear in popular software packages, including plotting product-limit survival curves, hazard plots, and probability plots in the context of censored data. The author integrates S-Plus and Minitab output throughout the text, along with a variety of real data sets so readers can see how the theory and methods are applied. He also incorporates exercises in each chapter that provide valuable problem-solving experience. In addition to all of this, the book also brings to light the most recent linear regression techniques. Most importantly, it includes a definitive account of the Buckley-James method for censored linear regression, found to be the best performing method when a Cox proportional hazards method is not appropriate. Applying the theories of survival analysis and reliability requires more background and experience than students typically receive at the undergraduate level. Mastering the contents of this book will help prepare students to begin performing research in survival analysis and reliability and provide seasoned practitioners with a deeper understanding of the field.
Author | : Toby Miller |
Publisher | : |
Total Pages | : |
Release | : 1997-08 |
Genre | : |
ISBN | : 9780471252184 |
Download Survival Analysis Book in PDF, ePub and Kindle
Author | : D.R. Cox |
Publisher | : Routledge |
Total Pages | : 240 |
Release | : 2018-02-19 |
Genre | : Mathematics |
ISBN | : 1351466739 |
Download Analysis of Binary Data Book in PDF, ePub and Kindle
The first edition of this book (1970) set out a systematic basis for the analysis of binary data and in particular for the study of how the probability of 'success' depends on explanatory variables. The first edition has been widely used and the general level and style have been preserved in the second edition, which contains a substantial amount of new material. This amplifies matters dealt with only cryptically in the first edition and includes many more recent developments. In addition the whole material has been reorganized, in particular to put more emphasis on m.aximum likelihood methods. There are nearly 60 further results and exercises. The main points are illustrated by practical examples, many of them not in the first edition, and some general essential background material is set out in new Appendices.
Author | : Göran Broström |
Publisher | : CRC Press |
Total Pages | : 238 |
Release | : 2018-09-03 |
Genre | : Mathematics |
ISBN | : 1315360527 |
Download Event History Analysis with R Book in PDF, ePub and Kindle
With an emphasis on social science applications, Event History Analysis with R presents an introduction to survival and event history analysis using real-life examples. Keeping mathematical details to a minimum, the book covers key topics, including both discrete and continuous time data, parametric proportional hazards, and accelerated failure times. Features Introduces parametric proportional hazards models with baseline distributions like the Weibull, Gompertz, Lognormal, and Piecewise constant hazard distributions, in addition to traditional Cox regression Presents mathematical details as well as technical material in an appendix Includes real examples with applications in demography, econometrics, and epidemiology Provides a dedicated R package, eha, containing special treatments, including making cuts in the Lexis diagram, creating communal covariates, and creating period statistics A much-needed primer, Event History Analysis with R is a didactically excellent resource for students and practitioners of applied event history and survival analysis.
Author | : Jianguo Sun |
Publisher | : Springer Science & Business Media |
Total Pages | : 283 |
Release | : 2013-10-09 |
Genre | : Medical |
ISBN | : 1461487153 |
Download Statistical Analysis of Panel Count Data Book in PDF, ePub and Kindle
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.