Modeling Survival Data
DOWNLOAD
Download Modeling Survival Data PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Modeling Survival Data book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Modeling Survival Data Extending The Cox Model
DOWNLOAD
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.
Extending the Cox Model is aimed at researchers, practitioners, and graduate students who have some exposure to traditional methods of survival analysis. The emphasis is on semiparametric methods based on the proportional hazards model. The inclusion of examples with SAS and S-PLUS code will make the book accessible to most working statisticians.
Modeling Survival Data Extending The Cox Model
DOWNLOAD
Author : Terry M. Therneau
language : en
Publisher: Springer Science & Business Media
Release Date : 2000-08-11
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 2000-08-11 with Mathematics categories.
Extending the Cox Model is aimed at researchers, practitioners, and graduate students who have some exposure to traditional methods of survival analysis. The emphasis is on semiparametric methods based on the proportional hazards model. The inclusion of examples with SAS and S-PLUS code will make the book accessible to most working statisticians.
Modelling Survival Data In Medical Research
DOWNLOAD
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
Modeling Survival Data Using Frailty Models
DOWNLOAD
Author : David D. Hanagal
language : en
Publisher: Springer Nature
Release Date : 2019-11-16
Modeling Survival Data Using Frailty Models written by David D. Hanagal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-16 with Medical categories.
This book presents the basic concepts of survival analysis and frailty models, covering both fundamental and advanced topics. It focuses on applications of statistical tools in biology and medicine, highlighting the latest frailty-model methodologies and applications in these areas. After explaining the basic concepts of survival analysis, the book goes on to discuss shared, bivariate, and correlated frailty models and their applications. It also features nine datasets that have been analyzed using the R statistical package. Covering recent topics, not addressed elsewhere in the literature, this book is of immense use to scientists, researchers, students and teachers.
Survival Analysis
DOWNLOAD
Author : Xian Liu
language : en
Publisher: John Wiley & Sons
Release Date : 2012-06-13
Survival Analysis written by Xian Liu 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 2012-06-13 with Mathematics categories.
Survival analysis concerns sequential occurrences of events governed by probabilistic laws. Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis. Assumes only a minimal knowledge of SAS whilst enabling more experienced users to learn new techniques of data input and manipulation. Provides numerous examples of SAS code to illustrate each of the methods, along with step-by-step instructions to perform each technique. Highlights the strengths and limitations of each technique covered. Covering a wide scope of survival techniques and methods, from the introductory to the advanced, this book can be used as a useful reference book for planners, researchers, and professors who are working in settings involving various lifetime events. Scientists interested in survival analysis should find it a useful guidebook for the incorporation of survival data and methods into their projects.
Applied Survival Analysis
DOWNLOAD
Author : David W. Hosmer, Jr.
language : en
Publisher: John Wiley & Sons
Release Date : 2008-03-07
Applied Survival Analysis written by David W. Hosmer, Jr. 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 2008-03-07 with Mathematics categories.
THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA—NOW IN A VALUABLE NEW EDITION Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research. This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data. Features of the Second Edition include: Expanded coverage of interactions and the covariate-adjusted survival functions The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques New discussion of variable selection with multivariable fractional polynomials Further exploration of time-varying covariates, complex with examples Additional treatment of the exponential, Weibull, and log-logistic parametric regression models Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values New examples and exercises at the end of each chapter Analyses throughout the text are performed using Stata® Version 9, and an accompanying FTP site contains the data sets used in the book. Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.
Statistical Modelling Of Survival Data With Random Effects
DOWNLOAD
Author : Il Do Ha
language : en
Publisher: Springer
Release Date : 2018-01-02
Statistical Modelling Of Survival Data With Random Effects written by Il Do Ha and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-02 with Mathematics categories.
This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (“frailtyHL”), while the real-world data examples together with an R package, “frailtyHL” in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to researchers in medical and genetics fields, graduate students, and PhD (bio) statisticians.
Dynamic Regression Models For Survival Data
DOWNLOAD
Author : Torben Martinussen
language : en
Publisher: Springer
Release Date : 2010-11-23
Dynamic Regression Models For Survival Data written by Torben Martinussen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-23 with Medical categories.
This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying effects of explanatory variables. Use of the suggested models and methods is illustrated on real data examples, using the R-package timereg developed by the authors, which is applied throughout the book with worked examples for the data sets.
Lifetime Data Models In Reliability And Survival Analysis
DOWNLOAD
Author : Nicholas P. Jewell
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Lifetime Data Models In Reliability And Survival Analysis written by Nicholas P. Jewell 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 2013-04-17 with Mathematics categories.
Statistical models and methods for lifetime and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, actuarial science, engineering, economics, management, and the social sciences. For example, closely related statistical methods have been applied to the study of the incubation period of diseases such as AIDS, the remission time of cancers, life tables, the time-to-failure of engineering systems, employment duration, and the length of marriages. This volume contains a selection of papers based on the 1994 International Research Conference on Lifetime Data Models in Reliability and Survival Analysis, held at Harvard University. The conference brought together a varied group of researchers and practitioners to advance and promote statistical science in the many fields that deal with lifetime and other time-to-event-data. The volume illustrates the depth and diversity of the field. A few of the authors have published their conference presentations in the new journal Lifetime Data Analysis (Kluwer Academic Publishers).
Advanced Survival Models
DOWNLOAD
Author : Catherine Legrand
language : en
Publisher: CRC Press
Release Date : 2021-03-22
Advanced Survival Models written by Catherine Legrand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-22 with Mathematics categories.
Survival data analysis is a very broad field of statistics, encompassing a large variety of methods used in a wide range of applications, and in particular in medical research. During the last twenty years, several extensions of "classical" survival models have been developed to address particular situations often encountered in practice. This book aims to gather in a single reference the most commonly used extensions, such as frailty models (in case of unobserved heterogeneity or clustered data), cure models (when a fraction of the population will not experience the event of interest), competing risk models (in case of different types of event), and joint survival models for a time-to-event endpoint and a longitudinal outcome. Features Presents state-of-the art approaches for different advanced survival models including frailty models, cure models, competing risk models and joint models for a longitudinal and a survival outcome Uses consistent notation throughout the book for the different techniques presented Explains in which situation each of these models should be used, and how they are linked to specific research questions Focuses on the understanding of the models, their implementation, and their interpretation, with an appropriate level of methodological development for masters students and applied statisticians Provides references to existing R packages and SAS procedure or macros, and illustrates the use of the main ones on real datasets This book is primarily aimed at applied statisticians and graduate students of statistics and biostatistics. It can also serve as an introductory reference for methodological researchers interested in the main extensions of classical survival analysis.