Multi-State Survival Models for Interval-Censored Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multi-State Survival Models for Interval-Censored Data write by Ardo van den Hout. This book was released on 2016-11-25. Multi-State Survival Models for Interval-Censored Data available in PDF, EPUB and Kindle. 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.
Competing Risks and Multistate Models with R
Competing Risks and Multistate Models with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Competing Risks and Multistate Models with R write by Jan Beyersmann. This book was released on 2011-11-18. Competing Risks and Multistate Models with R available in PDF, EPUB and Kindle. 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.
Introducing Survival and Event History Analysis
Introducing Survival and Event History Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introducing Survival and Event History Analysis write by Melinda Mills. This book was released on 2011-01-19. Introducing Survival and Event History Analysis available in PDF, EPUB and Kindle. 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
Analysis of Multivariate Survival Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Analysis of Multivariate Survival Data write by Philip Hougaard. This book was released on 2012-12-06. Analysis of Multivariate Survival Data available in PDF, EPUB and Kindle. 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
Statistical Models Based on Counting Processes - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Models Based on Counting Processes write by Per K. Andersen. This book was released on 2012-12-06. Statistical Models Based on Counting Processes available in PDF, EPUB and Kindle. 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.
