Joint Models For Longitudinal And Time To Event Data

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Joint Models for Longitudinal and Time-to-Event Data

Dimitris Rizopoulos
Joint Models for Longitudinal and Time to Event Data Book PDF

Author : Dimitris Rizopoulos
Publisher : CRC Press
Page : 279 pages
File Size : 55,5 Mb
Release : 2012-06-22
Category : Mathematics
ISBN : 9781439872864

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Joint Models for Longitudinal and Time-to-Event Data by Dimitris Rizopoulos Pdf

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

Robert Elashoff,Gang li,Ning Li
Joint Modeling of Longitudinal and Time to Event Data Book PDF

Author : Robert Elashoff,Gang li,Ning Li
Publisher : CRC Press
Page : 254 pages
File Size : 42,6 Mb
Release : 2016-10-04
Category : Mathematics
ISBN : 9781315357188

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Joint Modeling of Longitudinal and Time-to-Event Data by Robert Elashoff,Gang li,Ning Li Pdf

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

Joseph G. Ibrahim,Ming-Hui Chen,Debajyoti Sinha
Bayesian Survival Analysis Book PDF

Author : Joseph G. Ibrahim,Ming-Hui Chen,Debajyoti Sinha
Publisher : Springer Science & Business Media
Page : 494 pages
File Size : 55,8 Mb
Release : 2013-03-09
Category : Medical
ISBN : 9781475734478

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Bayesian Survival Analysis by Joseph G. Ibrahim,Ming-Hui Chen,Debajyoti Sinha Pdf

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.

Advanced Survival Models

Catherine Legrand
Advanced Survival Models Book PDF

Author : Catherine Legrand
Publisher : CRC Press
Page : 361 pages
File Size : 40,5 Mb
Release : 2021-03-22
Category : Mathematics
ISBN : 9780429622557

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Advanced Survival Models by Catherine Legrand Pdf

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.

Analysis of Longitudinal Data

Peter Diggle,Patrick Heagerty,Kung-Yee Liang,Scott Zeger
Analysis of Longitudinal Data Book PDF

Author : Peter Diggle,Patrick Heagerty,Kung-Yee Liang,Scott Zeger
Publisher : Oxford University Press, USA
Page : 397 pages
File Size : 46,8 Mb
Release : 2013-03-14
Category : Language Arts & Disciplines
ISBN : 9780199676750

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Analysis of Longitudinal Data by Peter Diggle,Patrick Heagerty,Kung-Yee Liang,Scott Zeger Pdf

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.

Longitudinal Data Analysis

Garrett Fitzmaurice,Marie Davidian,Geert Verbeke,Geert Molenberghs
Longitudinal Data Analysis Book PDF

Author : Garrett Fitzmaurice,Marie Davidian,Geert Verbeke,Geert Molenberghs
Publisher : CRC Press
Page : 633 pages
File Size : 40,8 Mb
Release : 2008-08-11
Category : Mathematics
ISBN : 9781420011579

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Longitudinal Data Analysis by Garrett Fitzmaurice,Marie Davidian,Geert Verbeke,Geert Molenberghs Pdf

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

Mixed Effects Models for Complex Data

Lang Wu
Mixed Effects Models for Complex Data Book PDF

Author : Lang Wu
Publisher : CRC Press
Page : 431 pages
File Size : 42,7 Mb
Release : 2009-11-11
Category : Mathematics
ISBN : 1420074083

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Mixed Effects Models for Complex Data by Lang Wu Pdf

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.

Modeling Survival Data: Extending the Cox Model

Terry M. Therneau,Patricia M. Grambsch
Modeling Survival Data Extending the Cox Model Book PDF

Author : Terry M. Therneau,Patricia M. Grambsch
Publisher : Springer Science & Business Media
Page : 356 pages
File Size : 47,8 Mb
Release : 2013-11-11
Category : Mathematics
ISBN : 9781475732948

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Modeling Survival Data: Extending the Cox Model by Terry M. Therneau,Patricia M. Grambsch Pdf

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.

The Frailty Model

Luc Duchateau,Paul Janssen
The Frailty Model Book PDF

Author : Luc Duchateau,Paul Janssen
Publisher : Springer Science & Business Media
Page : 316 pages
File Size : 49,8 Mb
Release : 2007-10-23
Category : Mathematics
ISBN : 9780387728353

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The Frailty Model by Luc Duchateau,Paul Janssen Pdf

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.

Cure Models

Yingwei Peng,Binbing Yu
Cure Models Book PDF

Author : Yingwei Peng,Binbing Yu
Publisher : CRC Press
Page : 268 pages
File Size : 40,7 Mb
Release : 2021-03-22
Category : Mathematics
ISBN : 9780429629686

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Cure Models by Yingwei Peng,Binbing Yu Pdf

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

John P. Klein,Hans C. van Houwelingen,Joseph G. Ibrahim,Thomas H. Scheike
Handbook of Survival Analysis Book PDF

Author : John P. Klein,Hans C. van Houwelingen,Joseph G. Ibrahim,Thomas H. Scheike
Publisher : CRC Press
Page : 635 pages
File Size : 51,5 Mb
Release : 2016-04-19
Category : Mathematics
ISBN : 9781466555679

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Handbook of Survival Analysis by John P. Klein,Hans C. van Houwelingen,Joseph G. Ibrahim,Thomas H. Scheike Pdf

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

Applied Longitudinal Data Analysis for Epidemiology

Jos W. R. Twisk
Applied Longitudinal Data Analysis for Epidemiology Book PDF

Author : Jos W. R. Twisk
Publisher : Cambridge University Press
Page : 337 pages
File Size : 43,9 Mb
Release : 2013-05-09
Category : Medical
ISBN : 9781107030039

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Applied Longitudinal Data Analysis for Epidemiology by Jos W. R. Twisk Pdf

A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.

AIDS Epidemiology

Nicholas P. Jewell,Klaus Dietz,Vernon T. Farewell
AIDS Epidemiology Book PDF

Author : Nicholas P. Jewell,Klaus Dietz,Vernon T. Farewell
Publisher : Springer Science & Business Media
Page : 413 pages
File Size : 47,8 Mb
Release : 2013-04-17
Category : Medical
ISBN : 9781475712292

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AIDS Epidemiology by Nicholas P. Jewell,Klaus Dietz,Vernon T. Farewell Pdf

In 1974, the Societal Institute of the Mathematical Sciences (SIMS) initiated a series of five-day Research Application Conferences (RAC's) at Alta, Utah, for the purpose of probing in depth societal fields in light of their receptivity to mathematical and statistical analysis. The first eleven conferences addressed ecosystems, epidemiology, energy, environmental health, time series and ecological processes, energy and health, energy conversion and fluid mechanics, environmental epidemiology: risk assessment, atomic bomb survival data: utilization and analysis, modem statistical methods in chronic disease epidemiology and scientific issues in quantitative cancer risk assess ment. These Proceedings are a result of the twelfth conference on Statistical Methodology for Study of the AIDS Epidemic which was held in 1991 at the Mathematical Sciences Research Institute, Berkeley, California. For five days, 45 speakers and observers contributed their expertise in the relevant biology and statistics. The presentations were timely and the discussion was both enlightening and at times spirited. Members of the Program Committee for the Conference were Klaus Dietz (University of Tiibingen, Germany), Vernon T. Farewell (University of Waterloo, Ontario), and Nicholas P. Jewell (University of California, Berke ley) (Chair). The Conference was supported by a grant to SIMS from the National Institute of Drug Abuse. D. L. Thomsen, Jr.

Maximum Likelihood Estimation with Stata, Fourth Edition

William Gould,Jeffrey Pitblado,Brian Poi
Maximum Likelihood Estimation with Stata Fourth Edition Book PDF

Author : William Gould,Jeffrey Pitblado,Brian Poi
Publisher : Stata Press
Page : 352 pages
File Size : 46,6 Mb
Release : 2010-10-27
Category : Mathematics
ISBN : 1597180785

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Maximum Likelihood Estimation with Stata, Fourth Edition by William Gould,Jeffrey Pitblado,Brian Poi Pdf

Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.

Dynamical Biostatistical Models

DANIEL. JACQMIN-GADDA COMMENGES (HELENE.),Helene Jacqmin-Gadda
Dynamical Biostatistical Models Book PDF

Author : DANIEL. JACQMIN-GADDA COMMENGES (HELENE.),Helene Jacqmin-Gadda
Publisher : CRC Press
Page : 408 pages
File Size : 41,5 Mb
Release : 2020-12-18
Category : Electronic
ISBN : 0367737744

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Dynamical Biostatistical Models by DANIEL. JACQMIN-GADDA COMMENGES (HELENE.),Helene Jacqmin-Gadda Pdf

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 applied using SAS or R software. The book describes advanced regression models that include the time dimension, such as mixed-effect models, survival models, multistate models, and joint models for repeated measures and time-to-event data. It also explores the possibility of unifying these models through a stochastic process point of view and introduces the dynamic approach to causal inference. Drawing on much of their own extensive research, the authors use three main examples throughout the text to illustrate epidemiological questions and methodological issues. Readers will see how each method is applied to real data and how to interpret the results.