Joint Modeling Of Longitudinal And Time To Event Data

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Joint Models for Longitudinal and Time-to-Event Data

Author : Dimitris Rizopoulos
Publisher : CRC Press
ISBN 13 : 1439872864
Total Pages : 279 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Joint Models for Longitudinal and Time-to-Event Data by : Dimitris Rizopoulos

Download or read book Joint Models for Longitudinal and Time-to-Event Data written by Dimitris Rizopoulos and published by CRC Press. This book was released on 2012-06-22 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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/

Joint Modeling of Longitudinal and Time-to-Event Data

Author : Robert Elashoff
Publisher : CRC Press
ISBN 13 : 1439807833
Total Pages : 262 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Joint Modeling of Longitudinal and Time-to-Event Data by : Robert Elashoff

Download or read book Joint Modeling of Longitudinal and Time-to-Event Data written by Robert Elashoff and published by CRC Press. This book was released on 2016-10-04 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website. This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

Bayesian Survival Analysis

Author : Joseph G. Ibrahim
Publisher : Springer Science & Business Media
ISBN 13 : 1475734476
Total Pages : 494 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Bayesian Survival Analysis by : Joseph G. Ibrahim

Download or read book Bayesian Survival Analysis written by Joseph G. Ibrahim and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. It presents a balance between theory and applications, and for each class of models discussed, detailed examples and analyses from case studies are presented whenever possible. The applications are all from the health sciences, including cancer, AIDS, and the environment.

Longitudinal Data Analysis

Author : Garrett Fitzmaurice
Publisher : CRC Press
ISBN 13 : 142001157X
Total Pages : 633 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Longitudinal Data Analysis by : Garrett Fitzmaurice

Download or read book Longitudinal Data Analysis written by Garrett Fitzmaurice and published by CRC Press. This book was released on 2008-08-11 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory

Joint Models for Longitudinal and Time-to-Event Data

Author : Dimitris Rizopoulos
Publisher : CRC Press
ISBN 13 : 1439872872
Total Pages : 274 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Joint Models for Longitudinal and Time-to-Event Data by : Dimitris Rizopoulos

Analysis of Longitudinal Data

Author : Peter Diggle
Publisher : Oxford University Press, USA
ISBN 13 : 0199676755
Total Pages : 397 pages
Book Rating : 4.1/5 (996 download)

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Book Synopsis Analysis of Longitudinal Data by : Peter Diggle

Download or read book Analysis of Longitudinal Data written by Peter Diggle and published by Oxford University Press, USA. This book was released on 2013-03-14 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.

Mixed Effects Models for Complex Data

Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

Advanced Survival Models

Author : Catherine Legrand
Publisher : CRC Press
ISBN 13 : 0429622554
Total Pages : 361 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Advanced Survival Models by : Catherine Legrand

Download or read book Advanced Survival Models written by Catherine Legrand and published by CRC Press. This book was released on 2021-03-22 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

The Frailty Model

Author : Luc Duchateau
Publisher : Springer Science & Business Media
ISBN 13 : 038772835X
Total Pages : 329 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis The Frailty Model by : Luc Duchateau

Download or read book The Frailty Model written by Luc Duchateau and published by Springer Science & Business Media. This book was released on 2007-10-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Dynamical Biostatistical Models

Author : Daniel Commenges
Publisher : CRC Press
ISBN 13 : 1498729681
Total Pages : 391 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Dynamical Biostatistical Models by : Daniel Commenges

Download or read book Dynamical Biostatistical Models written by Daniel Commenges and published by CRC Press. This book was released on 2015-10-02 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamical Biostatistical Models presents statistical models and methods for the analysis of longitudinal data. The book focuses on models for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. Most of the advanced methods, such as multistate and joint models, can be ap

Cure Models

Author : Yingwei Peng
Publisher : CRC Press
ISBN 13 : 0429629680
Total Pages : 268 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Cure Models by : Yingwei Peng

Download or read book Cure Models written by Yingwei Peng and published by CRC Press. This book was released on 2021-03-22 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cure Models: Methods, Applications and Implementation is the first book in the last 25 years that provides a comprehensive and systematic introduction to the basics of modern cure models, including estimation, inference, and software. This book is useful for statistical researchers and graduate students, and practitioners in other disciplines to have a thorough review of modern cure model methodology and to seek appropriate cure models in applications. The prerequisites of this book include some basic knowledge of statistical modeling, survival models, and R and SAS for data analysis. The book features real-world examples from clinical trials and population-based studies and a detailed introduction to R packages, SAS macros, and WinBUGS programs to fit some cure models. The main topics covered include the foundation of statistical estimation and inference of cure models for independent and right-censored survival data, cure modeling for multivariate, recurrent-event, and competing-risks survival data, and joint modeling with longitudinal data, statistical testing for the existence and difference of cure rates and sufficient follow-up, new developments in Bayesian cure models, applications of cure models in public health research and clinical trials.

Handbook of Survival Analysis

Author : John P. Klein
Publisher : CRC Press
ISBN 13 : 146655567X
Total Pages : 635 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Handbook of Survival Analysis by : John P. Klein

Download or read book Handbook of Survival Analysis written by John P. Klein and published by CRC Press. This book was released on 2016-04-19 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time. With chapters written by leading researchers in the field, the handbook focuses on advances in survival analysis techniques, covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers, the book provides: An introduction to various areas in survival analysis for graduate students and novices A reference to modern investigations into survival analysis for more established researchers A text or supplement for a second or advanced course in survival analysis A useful guide to statistical methods for analyzing survival data experiments for practicing statisticians

Missing Data in Clinical Studies

Author : Geert Molenberghs
Publisher : John Wiley & Sons
ISBN 13 : 9780470510438
Total Pages : 526 pages
Book Rating : 4.5/5 (14 download)

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Book Synopsis Missing Data in Clinical Studies by : Geert Molenberghs

Download or read book Missing Data in Clinical Studies written by Geert Molenberghs and published by John Wiley & Sons. This book was released on 2007-04-04 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing Data in Clinical Studies provides a comprehensive account of the problems arising when data from clinical and related studies are incomplete, and presents the reader with approaches to effectively address them. The text provides a critique of conventional and simple methods before moving on to discuss more advanced approaches. The authors focus on practical and modeling concepts, providing an extensive set of case studies to illustrate the problems described. Provides a practical guide to the analysis of clinical trials and related studies with missing data. Examines the problems caused by missing data, enabling a complete understanding of how to overcome them. Presents conventional, simple methods to tackle these problems, before addressing more advanced approaches, including sensitivity analysis, and the MAR missingness mechanism. Illustrated throughout with real-life case studies and worked examples from clinical trials. Details the use and implementation of the necessary statistical software, primarily SAS. Missing Data in Clinical Studies has been developed through a series of courses and lectures. Its practical approach will appeal to applied statisticians and biomedical researchers, in particular those in the biopharmaceutical industry, medical and public health organisations. Graduate students of biostatistics will also find much of benefit.

Joint Modeling of Longitudinal Data and Time-to-event Data

Author : Jijun Zhu
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Joint Modeling of Longitudinal Data and Time-to-event Data by : Jijun Zhu

Download or read book Joint Modeling of Longitudinal Data and Time-to-event Data written by Jijun Zhu and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Linear Mixed Models for Longitudinal Data

Author : Geert Verbeke
Publisher : Springer Science & Business Media
ISBN 13 : 1441903003
Total Pages : 579 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Linear Mixed Models for Longitudinal Data by : Geert Verbeke

Download or read book Linear Mixed Models for Longitudinal Data written by Geert Verbeke and published by Springer Science & Business Media. This book was released on 2009-05-12 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.

Applied Longitudinal Data Analysis

Author : Judith D. Singer
Publisher : Oxford University Press
ISBN 13 : 9780195152968
Total Pages : 672 pages
Book Rating : 4.1/5 (529 download)

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Book Synopsis Applied Longitudinal Data Analysis by : Judith D. Singer

Download or read book Applied Longitudinal Data Analysis written by Judith D. Singer and published by Oxford University Press. This book was released on 2003-03-27 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives.

Modeling Discrete Time-to-Event Data

Author : Gerhard Tutz
Publisher : Springer
ISBN 13 : 3319281585
Total Pages : 252 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Modeling Discrete Time-to-Event Data by : Gerhard Tutz

Download or read book Modeling Discrete Time-to-Event Data written by Gerhard Tutz and published by Springer. This book was released on 2016-06-14 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are explained. Each section includes a set of exercises on the respective topics. Various functions and tools for the analysis of discrete survival data are collected in the R package discSurv that accompanies the book.