Models For Multi State Survival Data

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Multi-State Survival Models for Interval-Censored Data

Author : Ardo van den Hout
Publisher : CRC Press
ISBN 13 : 1315356732
Total Pages : 181 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Multi-State Survival Models for Interval-Censored Data by : Ardo van den Hout

Download or read book Multi-State Survival Models for Interval-Censored Data written by Ardo van den Hout and published by CRC Press. This book was released on 2016-11-25 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book is a three-state process for dementia and survival in the older population. This process is described by an illness-death model with a dementia-free state, a dementia state, and a dead state. Statistical modelling of a multi-state process can investigate potential associations between the risk of moving to the next state and variables such as age, gender, or education. A model can also be used to predict the multi-state process. The methods are for longitudinal data subject to interval censoring. Depending on the definition of a state, it is possible that the time of the transition into a state is not observed exactly. However, when longitudinal data are available the transition time may be known to lie in the time interval defined by two successive observations. Such an interval-censored observation scheme can be taken into account in the statistical inference. Multi-state modelling is an elegant combination of statistical inference and the theory of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide range of applications.

Models for Multi-State Survival Data

Author : Per Kragh Andersen
Publisher : CRC Press
ISBN 13 : 0429642261
Total Pages : 293 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Models for Multi-State Survival Data by : Per Kragh Andersen

Download or read book Models for Multi-State Survival Data written by Per Kragh Andersen and published by CRC Press. This book was released on 2023-10-11 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time. They find application particularly in biostatistics, medicine, and public health. The book includes mathematical detail which can be skipped by readers more interested in the practical examples. It is aimed at biostatisticians and at readers with an interest in the topic having a more applied background, such as epidemiology. This book builds on several courses the authors have taught on the subject. Key Features: · Intensity-based and marginal models. · Survival data, competing risks, illness-death models, recurrent events. · Includes a full chapter on pseudo-values. · Intuitive introductions and mathematical details. · Practical examples of event history data. · Exercises. Software code in R and SAS and the data used in the book can be found on the book’s webpage.

Competing Risks and Multistate Models with R

Author : Jan Beyersmann
Publisher : Springer Science & Business Media
ISBN 13 : 1461420350
Total Pages : 249 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Competing Risks and Multistate Models with R by : Jan Beyersmann

Download or read book Competing Risks and Multistate Models with R written by Jan Beyersmann and published by Springer Science & Business Media. This book was released on 2011-11-18 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.

Multi-State Survival Models for Interval-Censored Data

Author : Ardo van den Hout
Publisher : CRC Press
ISBN 13 : 1466568410
Total Pages : 257 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Multi-State Survival Models for Interval-Censored Data by : Ardo van den Hout

Download or read book Multi-State Survival Models for Interval-Censored Data written by Ardo van den Hout and published by CRC Press. This book was released on 2016-11-25 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book is a three-state process for dementia and survival in the older population. This process is described by an illness-death model with a dementia-free state, a dementia state, and a dead state. Statistical modelling of a multi-state process can investigate potential associations between the risk of moving to the next state and variables such as age, gender, or education. A model can also be used to predict the multi-state process. The methods are for longitudinal data subject to interval censoring. Depending on the definition of a state, it is possible that the time of the transition into a state is not observed exactly. However, when longitudinal data are available the transition time may be known to lie in the time interval defined by two successive observations. Such an interval-censored observation scheme can be taken into account in the statistical inference. Multi-state modelling is an elegant combination of statistical inference and the theory of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide range of applications.

Introducing Survival and Event History Analysis

Author : Melinda Mills
Publisher : SAGE
ISBN 13 : 1848601026
Total Pages : 301 pages
Book Rating : 4.8/5 (486 download)

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Book Synopsis Introducing Survival and Event History Analysis by : Melinda Mills

Download or read book Introducing Survival and Event History Analysis written by Melinda Mills and published by SAGE. This book was released on 2011-01-19 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an accessible, practical and comprehensive guide for researchers from multiple disciplines including biomedical, epidemiology, engineering and the social sciences. Written for accessibility, this book will appeal to students and researchers who want to understand the basics of survival and event history analysis and apply these methods without getting entangled in mathematical and theoretical technicalities. Inside, readers are offered a blueprint for their entire research project from data preparation to model selection and diagnostics. Engaging, easy to read, functional and packed with enlightening examples, ‘hands-on’ exercises, conversations with key scholars and resources for both students and instructors, this text allows researchers to quickly master advanced statistical techniques. It is written from the perspective of the ‘user’, making it suitable as both a self-learning tool and graduate-level textbook. Also included are up-to-date innovations in the field, including advancements in the assessment of model fit, unobserved heterogeneity, recurrent events and multilevel event history models. Practical instructions are also included for using the statistical programs of R, STATA and SPSS, enabling readers to replicate the examples described in the text.

Analysis of Multivariate Survival Data

Author : Philip Hougaard
Publisher : Springer Science & Business Media
ISBN 13 : 1461213045
Total Pages : 559 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Analysis of Multivariate Survival Data by : Philip Hougaard

Download or read book Analysis of Multivariate Survival Data written by Philip Hougaard and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing for multivariate times. As the field is rather new, the concepts and the possible types of data are described in detail. Four different approaches to the analysis of such data are presented from an applied point of view.

Statistical Models Based on Counting Processes

Author : Per K. Andersen
Publisher : Springer Science & Business Media
ISBN 13 : 1461243483
Total Pages : 779 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Statistical Models Based on Counting Processes by : Per K. Andersen

Download or read book Statistical Models Based on Counting Processes written by Per K. Andersen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern survival analysis and more general event history analysis may be effectively handled within the mathematical framework of counting processes. This book presents this theory, which has been the subject of intense research activity over the past 15 years. The exposition of the theory is integrated with careful presentation of many practical examples, drawn almost exclusively from the authors'own experience, with detailed numerical and graphical illustrations. Although Statistical Models Based on Counting Processes may be viewed as a research monograph for mathematical statisticians and biostatisticians, almost all the methods are given in concrete detail for use in practice by other mathematically oriented researchers studying event histories (demographers, econometricians, epidemiologists, actuarial mathematicians, reliability engineers and biologists). Much of the material has so far only been available in the journal literature (if at all), and so a wide variety of researchers will find this an invaluable survey of the subject.

Data Analysis with Competing Risks and Intermediate States

Author : Ronald B. Geskus
Publisher : CRC Press
ISBN 13 : 1466570369
Total Pages : 278 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Data Analysis with Competing Risks and Intermediate States by : Ronald B. Geskus

Download or read book Data Analysis with Competing Risks and Intermediate States written by Ronald B. Geskus and published by CRC Press. This book was released on 2015-07-14 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis with Competing Risks and Intermediate States explains when and how to use models and techniques for the analysis of competing risks and intermediate states. It covers the most recent insights on estimation techniques and discusses in detail how to interpret the obtained results.After introducing example studies from the biomedical and

Multistate Models for the Analysis of Life History Data

Author : Richard J Cook
Publisher : CRC Press
ISBN 13 : 1351646052
Total Pages : 524 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Multistate Models for the Analysis of Life History Data by : Richard J Cook

Download or read book Multistate Models for the Analysis of Life History Data written by Richard J Cook and published by CRC Press. This book was released on 2018-05-15 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multistate Models for the Analysis of Life History Data provides the first comprehensive treatment of multistate modeling and analysis, including parametric, nonparametric and semiparametric methods applicable to many types of life history data. Special models such as illness-death, competing risks and progressive processes are considered, as well as more complex models. The book provides both theoretical development and illustrations of analysis based on data from randomized trials and observational cohort studies in health research. It features: Discusses a wide range of applications of multistate models, Presents methods for both continuously and intermittently observed life history processes, Gives a thorough discussion of conditionally independent censoring and observation processes, Discusses models with random effects and joint models for two or more multistate processes, Discusses and illustrates software for multistate analysis that is available in R, Target audience includes those engaged in research and applications involving multistate models.

Multistate Analysis of Life Histories with R

Author : Frans Willekens
Publisher : Springer
ISBN 13 : 331908383X
Total Pages : 323 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Multistate Analysis of Life Histories with R by : Frans Willekens

Download or read book Multistate Analysis of Life Histories with R written by Frans Willekens and published by Springer. This book was released on 2014-09-11 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to multistate event history analysis. It is an extension of survival analysis, in which a single terminal event (endpoint) is considered and the time-to-event is studied. Multistate models focus on life histories or trajectories, conceptualized as sequences of states and sequences of transitions between states. Life histories are modeled as realizations of continuous-time Markov processes. The model parameters, transition rates, are estimated from data on event counts and populations at risk, using the statistical theory of counting processes. The Comprehensive R Network Archive (CRAN) includes several packages for multistate modeling. This book is about Biograph. The package is designed to (a) enhance exploratory analysis of life histories and (b) make multistate modeling accessible. The package incorporates utilities that connect to several packages for multistate modeling, including survival, eha, Epi, mvna,, mstate, msm, and TraMineR for sequence analysis. The book is a ‘hands-on’ presentation of Biograph and the packages listed. It is written from the perspective of the user. To help the user master the techniques and the software, a single data set is used to illustrate the methods and software. It is the subsample of the German Life History Survey, which was also used by Blossfeld and Rohwer in their popular textbook on event history modeling. Another data set, the Netherlands Family and Fertility Survey, is used to illustrate how Biograph can assist in answering questions on life paths of cohorts and individuals. The book is suitable as a textbook for graduate courses on event history analysis and introductory courses on competing risks and multistate models. It may also be used as a self-study book. The R code used in the book is available online. Frans Willekens is affiliated with the Max Planck Institute for Demographic Research (MPIDR) in Rostock, Germany. He is Emeritus Professor of Demography at the University of Groningen, a Honorary Fellow of the Netherlands Interdisciplinary Demographic Institute (NIDI) in the Hague, and a Research Associate of the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria. He is a member of Royal Netherlands Academy of Arts and Sciences (KNAW). He has contributed to the modeling and simulation of life histories, mainly in the context of population forecasting.

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

Dynamic Prediction in Clinical Survival Analysis

Author : Hans van Houwelingen
Publisher : CRC Press
ISBN 13 : 1439835438
Total Pages : 250 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Dynamic Prediction in Clinical Survival Analysis by : Hans van Houwelingen

Download or read book Dynamic Prediction in Clinical Survival Analysis written by Hans van Houwelingen and published by CRC Press. This book was released on 2011-11-09 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a huge amount of literature on statistical models for the prediction of survival after diagnosis of a wide range of diseases like cancer, cardiovascular disease, and chronic kidney disease. Current practice is to use prediction models based on the Cox proportional hazards model and to present those as static models for remaining lifetime a

The Statistical Analysis of Failure Time Data

Author : John D. Kalbfleisch
Publisher : John Wiley & Sons
ISBN 13 : 1118031237
Total Pages : 462 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis The Statistical Analysis of Failure Time Data by : John D. Kalbfleisch

Download or read book The Statistical Analysis of Failure Time Data written by John D. Kalbfleisch and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains additional discussion and examples on left truncationas well as material on more general censoring and truncationpatterns. Introduces the martingale and counting process formulation swillbe in a new chapter. Develops multivariate failure time data in a separate chapterand extends the material on Markov and semi Markovformulations. Presents new examples and applications of data analysis.

Multivariate Survival Analysis and Competing Risks

Author : Martin J. Crowder
Publisher : CRC Press
ISBN 13 : 1439875227
Total Pages : 402 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Multivariate Survival Analysis and Competing Risks by : Martin J. Crowder

Download or read book Multivariate Survival Analysis and Competing Risks written by Martin J. Crowder and published by CRC Press. This book was released on 2012-04-17 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate

Introducing Survival and Event History Analysis

Author : Melinda Mills
Publisher : SAGE Publications
ISBN 13 : 1848601026
Total Pages : 301 pages
Book Rating : 4.8/5 (486 download)

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Book Synopsis Introducing Survival and Event History Analysis by : Melinda Mills

Download or read book Introducing Survival and Event History Analysis written by Melinda Mills and published by SAGE Publications. This book was released on 2011-01-19 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an accessible, practical and comprehensive guide for researchers from multiple disciplines including biomedical, epidemiology, engineering and the social sciences. Written for accessibility, this book will appeal to students and researchers who want to understand the basics of survival and event history analysis and apply these methods without getting entangled in mathematical and theoretical technicalities. Inside, readers are offered a blueprint for their entire research project from data preparation to model selection and diagnostics. Engaging, easy to read, functional and packed with enlightening examples, ‘hands-on’ exercises, conversations with key scholars and resources for both students and instructors, this text allows researchers to quickly master advanced statistical techniques. It is written from the perspective of the ‘user’, making it suitable as both a self-learning tool and graduate-level textbook. Also included are up-to-date innovations in the field, including advancements in the assessment of model fit, unobserved heterogeneity, recurrent events and multilevel event history models. Practical instructions are also included for using the statistical programs of R, STATA and SPSS, enabling readers to replicate the examples described in the text.

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/

Statistical Modelling of Survival Data with Random Effects

Author : Il Do Ha
Publisher : Springer
ISBN 13 : 9811065578
Total Pages : 283 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Statistical Modelling of Survival Data with Random Effects by : Il Do Ha

Download or read book Statistical Modelling of Survival Data with Random Effects written by Il Do Ha and published by Springer. This book was released on 2018-01-02 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.