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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… Mehr…

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Multistate Analysis of Life Histories with R Frans Willekens Author - neues Buch

ISBN: 9783319083834

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… Mehr…

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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… Mehr…

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Detailangaben zum Buch - Multistate Analysis of Life Histories with R Frans Willekens Author


EAN (ISBN-13): 9783319083834
Erscheinungsjahr: 9
Herausgeber: Springer-Verlag New York, LLC Digital >16

Buch in der Datenbank seit 2014-11-21T15:45:54+01:00 (Berlin)
Detailseite zuletzt geändert am 2024-05-10T09:07:50+02:00 (Berlin)
ISBN/EAN: 9783319083834

ISBN - alternative Schreibweisen:
978-3-319-08383-4
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: willeke, blossfeld, archive history sciences, willekens
Titel des Buches: analysis


Daten vom Verlag:

Autor/in: Frans Willekens
Titel: Use R! Multistate Analysis of Life Histories with R
Verlag: Springer; Springer International Publishing
308 Seiten
Erscheinungsjahr: 2014-09-11
Cham; CH
Sprache: Englisch
53,49 € (DE)
55,00 € (AT)
67,00 CHF (CH)
Available
XXII, 308 p. 45 illus., 36 illus. in color.

EA; E107; eBook; Nonbooks, PBS / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Demography / Demographic methods; Epidemiology/Methods; Event histories; Multistate modeling; Survival analysis; B; Statistics; Statistics and Computing; Population and Demography; Epidemiology; Mathematics and Statistics; Mathematische und statistische Software; Bevölkerung und Demographie; Epidemiologie und medizinische Statistik; BC

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<, etm, 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 has contributed to the modeling and simulation of life histories, mainly in the context of population forecasting.
Presents a step-by-step procedure for investigating life histories using descriptive methods and statistical modeling, as well as the popular software language for statistical computing (R) For educational purposes, a single data set is used throughout the book: a subsample of the German Life History Survey (201 respondents) In the last chapter, a second data set is used: a subsample of the Netherlands Family and Fertility Survey (500 respondents) The appendix details how to start applying Biograph to other major data sets, including the Survey of Health, Ageing and Retirement in Europe (SHARE) and the Demographic and Health Survey Life history data is visualized using ggplot2 Includes supplementary material: sn.pub/extras

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