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Modeling Survival Data: Extending the Cox Model

Modeling Survival Data: Extending the Cox Model PDF Author: Terry M. Therneau
Publisher: Springer Science & Business Media
ISBN: 1475732945
Category : Mathematics
Languages : en
Pages : 356

Book Description
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.

Modeling Survival Data: Extending the Cox Model

Modeling Survival Data: Extending the Cox Model PDF Author: Terry M. Therneau
Publisher: Springer Science & Business Media
ISBN: 1475732945
Category : Mathematics
Languages : en
Pages : 356

Book Description
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.

Modeling Survival Data

Modeling Survival Data PDF Author: Terry M. Therneau
Publisher:
ISBN: 9781475732955
Category :
Languages : en
Pages : 368

Book Description


Modeling Survival Data:extending Cox Model

Modeling Survival Data:extending Cox Model PDF Author: t;grandosch therneau (o)
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description


Survival Analysis

Survival Analysis PDF Author: David G. Kleinbaum
Publisher: Springer Science & Business Media
ISBN: 1475725558
Category : Medical
Languages : en
Pages : 332

Book Description
A straightforward and easy-to-follow introduction to the main concepts and techniques of the subject. It is based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind. A "user-friendly" layout includes numerous illustrations and exercises and the book is written in such a way so as to enable readers learn directly without the assistance of a classroom instructor. Throughout, there is an emphasis on presenting each new topic backed by real examples of a survival analysis investigation, followed up with thorough analyses of real data sets. Each chapter concludes with practice exercises to help readers reinforce their understanding of the concepts covered, before going on to a more comprehensive test. Answers to both are included. Readers will enjoy David Kleinbaums style of presentation, making this an excellent introduction for all those coming to the subject for the first time.

The Frailty Model

The Frailty Model PDF Author: Luc Duchateau
Publisher: Springer Science & Business Media
ISBN: 038772835X
Category : Mathematics
Languages : en
Pages : 329

Book Description
Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website.

Modelling Survival Data in Medical Research

Modelling Survival Data in Medical Research PDF Author: David Collett
Publisher: CRC Press
ISBN: 1498731694
Category : Mathematics
Languages : en
Pages : 538

Book Description
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

Modelling Survival Data in Medical Research, Second Edition PDF Author: David Collett
Publisher: CRC Press
ISBN: 1584883251
Category : Mathematics
Languages : en
Pages : 413

Book Description
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.

The Cox Model and Its Applications

The Cox Model and Its Applications PDF Author: Mikhail Nikulin
Publisher: Springer
ISBN: 3662493322
Category : Mathematics
Languages : en
Pages : 131

Book Description
This book will be of interest to readers active in the fields of survival analysis, genetics, ecology, biology, demography, reliability and quality control. Since Sir David Cox’s pioneering work in 1972, the proportional hazards model has become the most important model in survival analysis. The success of the Cox model stimulated further studies in semiparametric and nonparametric theories, counting process models, study designs in epidemiology, and the development of many other regression models that could offer more flexible or more suitable approaches in data analysis. Flexible semiparametric regression models are increasingly being used to relate lifetime distributions to time-dependent explanatory variables. Throughout the book, various recent statistical models are developed in close connection with specific data from experimental studies in clinical trials or from observational studies.

An Introduction to Survival Analysis Using Stata, Second Edition

An Introduction to Survival Analysis Using Stata, Second Edition PDF Author: Mario Cleves
Publisher: Stata Press
ISBN: 1597180416
Category : Computers
Languages : en
Pages : 398

Book Description
"[This book] provides new researchers with the foundation for understanding the various approaches for analyzing time-to-event data. This book serves not only as a tutorial for those wishing to learn survival analysis but as a ... reference for experienced researchers ..."--Book jacket.

Joint Models for Longitudinal and Time-to-Event Data

Joint Models for Longitudinal and Time-to-Event Data PDF Author: Dimitris Rizopoulos
Publisher: CRC Press
ISBN: 1439872864
Category : Mathematics
Languages : en
Pages : 279

Book Description
In longitudinal studies it is often of interest to investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest, e.g., prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R provides a full treatment of random effects joint models for longitudinal and time-to-event outcomes that can be utilized to analyze such data. The content is primarily explanatory, focusing on applications of joint modeling, but sufficient mathematical details are provided to facilitate understanding of the key features of these models. All illustrations put forward can be implemented in the R programming language via the freely available package JM written by the author. All the R code used in the book is available at: http://jmr.r-forge.r-project.org/