Modelling Survival Data In Medical Research
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Modelling Survival Data In Medical Research
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Author : David Collett
language : en
Publisher: CRC Press
Release Date : 2015-05-04
Modelling Survival Data In Medical Research written by David Collett and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-04 with Mathematics categories.
Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research.Well known for its nontechnical style, this third edition contains new chapters on frailty models and their applications, competing risks, non-proportional hazards, and dependent censo
Modelling Survival Data In Medical Research Second Edition
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Author : David Collett
language : en
Publisher: CRC Press
Release Date : 2003-03-28
Modelling Survival Data In Medical Research Second Edition written by David Collett and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-03-28 with Mathematics categories.
Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in Medical Research has been thoroughly revised and updated to reflect the many developments and advances--particularly in software--made in the field over the last 10 years. Now, more than ever, it provides an outstanding text for upper-level and graduate courses in survival analysis, biostatistics, and time-to-event analysis.The treatment begins with an introduction to survival analysis and a description of four studies that lead to survival data. Subsequent chapters then use those data sets and others to illustrate the various analytical techniques applicable to such data, including the Cox regression model, the Weibull proportional hazards model, and others. This edition features a more detailed treatment of topics such as parametric models, accelerated failure time models, and analysis of interval-censored data. The author also focuses the software section on the use of SAS, summarising the methods used by the software to generate its output and examining that output in detail. Profusely illustrated with examples and written in the author's trademark, easy-to-follow style, Modelling Survival Data in Medical Research, Second Edition is a thorough, practical guide to survival analysis that reflects current statistical practices.
Modelling Survival Data In Medical Research
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Author : D. Collett
language : en
Publisher: Chapman and Hall/CRC
Release Date : 1994
Modelling Survival Data In Medical Research written by D. Collett and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.
An introduction to modelling survival data in medical research. It demonstrates how widely available computer software can be used in survival analysis. It seeks to provide sufficient methodological development for the reader to understand assumptions upon which techniques are based, and to help the reader to adapt the methodology to deal with non-standard problems.
Modelling Survival Data In Medical Research Third Edition
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Author : David Collett
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2014-12-11
Modelling Survival Data In Medical Research Third Edition written by David Collett and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-11 with Mathematics categories.
Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research. Well known for its nontechnical style, this third edition contains new chapters on frailty models and their applications, competing risks, non-proportional hazards, and dependent censoring. It also describes techniques for modelling the occurrence of multiple events and event history analysis. Earlier chapters are now expanded to include new material on a number of topics, including measures of predictive ability and flexible parametric models. Many new data sets and examples are included to illustrate how these techniques are used in modelling survival data. Bibliographic notes and suggestions for further reading are provided at the end of each chapter. Additional data sets to obtain a fuller appreciation of the methodology, or to be used as student exercises, are provided in the appendix. All data sets used in this book are also available in electronic format online. This book is an invaluable resource for statisticians in the pharmaceutical industry, professionals in medical research institutes, scientists and clinicians who are analyzing their own data, and students taking undergraduate or postgraduate courses in survival analysis.
Modelling Survival Data In Medical Research Second Edition
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Author : David Collett
language : en
Publisher:
Release Date : 2003
Modelling Survival Data In Medical Research Second Edition written by David Collett and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Modelling Survival Data In Medical Research
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Author : David Collett
language : en
Publisher:
Release Date : 1993
Modelling Survival Data In Medical Research written by David Collett and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Clinical trials categories.
Data collected on the time to an event-such as the death of a patient in a medical study-is known as survival data. The methods for analyzing survival data can also be used to analyze data on the time to events such as the recurrence of a disease or relief from symptoms. Modelling Survival Data in Medical Research begins with an introduction to survival analysis and a description of four studies in which survival data was obtained. These and other data sets are then used to illustrate the techniques presented in the following chapters, including the Cox and Weibull proportional hazards models; accelerated failure time models; models with time-dependent variables; interval-censored survival data; model checking; and use of statistical packages. Designed for statisticians in the pharmaceutical industry and medical research institutes, and for numerate scientists and clinicians analyzing their own data sets, this book also meets the need for an intermediate text which emphasizes the application of the methodology to survival data arising from medical studies.
Analysing Survival Data From Clinical Trials And Observational Studies
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Author : Ettore Marubini
language : en
Publisher: John Wiley & Sons
Release Date : 2004-07-02
Analysing Survival Data From Clinical Trials And Observational Studies written by Ettore Marubini 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 2004-07-02 with Mathematics categories.
A practical guide to methods of survival analysis for medical researchers with limited statistical experience. Methods and techniques described range from descriptive and exploratory analysis to multivariate regression methods. Uses illustrative data from actual clinical trials and observational studies to describe methods of analysing and reporting results. Also reviews the features and performance of statistical software available for applying the methods of analysis discussed.
Survival Analysis In Medicine And Genetics
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Author : Jialiang Li
language : en
Publisher: CRC Press
Release Date : 2013-06-04
Survival Analysis In Medicine And Genetics written by Jialiang Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-04 with Mathematics categories.
Using real data sets throughout, this text introduces the latest methods for analyzing high-dimensional survival data. With an emphasis on the applications of survival analysis techniques in genetics, it presents a statistical framework for burgeoning research in this area and offers a set of established approaches for statistical analysis. The book reveals a new way of looking at how predictors are associated with censored survival time and extracts novel statistical genetic methods for censored survival time outcome from the vast amount of research results in genomics.
Statistical Methods For Survival Data Analysis
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Author : Elisa T. Lee
language : en
Publisher: John Wiley & Sons
Release Date : 2013-09-23
Statistical Methods For Survival Data Analysis written by Elisa T. Lee 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 2013-09-23 with Mathematics categories.
Praise for the Third Edition “. . . an easy-to read introduction to survival analysis which covers the major concepts and techniques of the subject.” —Statistics in Medical Research Updated and expanded to reflect the latest developments, Statistical Methods for Survival Data Analysis, Fourth Edition continues to deliver a comprehensive introduction to the most commonly-used methods for analyzing survival data. Authored by a uniquely well-qualified author team, the Fourth Edition is a critically acclaimed guide to statistical methods with applications in clinical trials, epidemiology, areas of business, and the social sciences. The book features many real-world examples to illustrate applications within these various fields, although special consideration is given to the study of survival data in biomedical sciences. Emphasizing the latest research and providing the most up-to-date information regarding software applications in the field, Statistical Methods for Survival Data Analysis, Fourth Edition also includes: Marginal and random effect models for analyzing correlated censored or uncensored data Multiple types of two-sample and K-sample comparison analysis Updated treatment of parametric methods for regression model fitting with a new focus on accelerated failure time models Expanded coverage of the Cox proportional hazards model Exercises at the end of each chapter to deepen knowledge of the presented material Statistical Methods for Survival Data Analysis is an ideal text for upper-undergraduate and graduate-level courses on survival data analysis. The book is also an excellent resource for biomedical investigators, statisticians, and epidemiologists, as well as researchers in every field in which the analysis of survival data plays a role.
Modeling Survival Data Extending The Cox Model
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Author : Terry M. Therneau
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Modeling Survival Data Extending The Cox Model written by Terry M. Therneau 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 2013-11-11 with Mathematics categories.
This book is for statistical practitioners, particularly those who design and analyze studies for survival and event history data. Building on recent developments motivated by counting process and martingale theory, it shows the reader how to extend the Cox model to analyze multiple/correlated event data using marginal and random effects. The focus is on actual data examples, the analysis and interpretation of results, and computation. The book shows how these new methods can be implemented in SAS and S-Plus, including computer code, worked examples, and data sets.