Survival and Event History Analysis : A Process Point of View
Time-to-event data are ubiquitous in fields such as medicine, biology, demography, sociology, economics and reliability theory. Recently, a need to analyze more complex event histories has emerged. Examples are individuals that move among several states, frailty that makes some units fail before oth...
שמור ב:
| Auteurs principaux: | , , |
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| פורמט: | Livre numérique |
| שפה: | Anglais |
| יצא לאור: |
New York, NY :
Springer New York : Springer e-books
[20..].
Cham : Springer Nature |
| סדרה: | Statistics for Biology and Health
|
| נושאים: | |
| גישה מקוונת: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| הערה: |
L'impression du document génère 549 p. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Survival and event history analysis, a process point of view, by Odd Aalen, Ørnulf Borgan, Håkon K. Gjessing, 2008, New York, Springer, 1 volume (XVIII-539 pages), Statistics for biology and health, 978-0-387-20287-7 |
| LEADER | 05642nam a22004697a 4500 | ||
|---|---|---|---|
| 001 | 940753 | ||
| 008 | 081113q2000 xxe ||| |||| 00| 0 eng d | ||
| 009 | PPN129059595 | ||
| 020 | |a 9780387685601 | ||
| 041 | 0 | |a eng | |
| 082 | |a 519.2 | ||
| 084 | |a 62N01. 2010 | ||
| 084 | |a 60G55. 2010 | ||
| 084 | |a 62N05. 2010 | ||
| 100 | 1 | |a Aalen, Odd Olai, |d 1947- | |
| 245 | 1 | 0 | |a Survival and Event History Analysis : |b A Process Point of View |c Odd O. Aalen, Ørnulf Borgan, Håkon K. Gjessing. |
| 260 | |a New York, NY : |b Springer New York : |b Springer e-books. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 1 | |a Statistics for Biology and Health | |
| 500 | |a L'impression du document génère 549 p. | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 504 | |a Bibliogr. Index | ||
| 505 | 1 | |a An introduction to survival and event history analysis Stochastic processes in event history analysis Nonparametric analysis of survival and event history data Regression models Parametric counting process models Unobserved heterogeneity: The odd effects of frailty Multivariate frailty models Marginal and dynamic models for recurrent events and clustered survival data Causality First passage time models: Understanding the shape of the hazard rate Diffusion and L#x00E9;vy process models for dynamic frailty | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a Time-to-event data are ubiquitous in fields such as medicine, biology, demography, sociology, economics and reliability theory. Recently, a need to analyze more complex event histories has emerged. Examples are individuals that move among several states, frailty that makes some units fail before others, internal time-dependent covariates, and the estimation of causal effects from observational data. The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data manifests itself fully. The common denominator of such models is stochastic processes. The authors show how counting processes, martingales, and stochastic integrals fit very nicely with censored data. Beginning with standard analyses such as Kaplan-Meier plots and Cox regression, the presentation progresses to the additive hazard model and recurrent event data. Stochastic processes are also used as natural models for individual frailty; they allow sensible interpretations of a number of surprising artifacts seen in population data. The stochastic process framework is naturally connected to causality. The authors show how dynamic path analyses can incorporate many modern causality ideas in a framework that takes the time aspect seriously. To make the material accessible to the reader, a large number of practical examples, mainly from medicine, are developed in detail. Stochastic processes are introduced in an intuitive and non-technical manner. The book is aimed at investigators who use event history methods and want a better understanding of the statistical concepts. It is suitable as a textbook for graduate courses in statistics and biostatistics. Odd O. Aalen is professor of medical statistics at the University of Oslo, Norway. His Ph.D. from the University of California, Berkeley in 1975 introduced counting processes and martingales in event history analysis. He has also contributed to numerous other areas of event history analysis, such as additive hazards regression, frailty, and causality through dynamic modeling. Ørnulf Borgan is professor of statistics at the University of Oslo, Norway. Since his Ph.D. in 1984 he has contributed extensively to event history analysis. He is co-author of the monograph Statistical Models Based on Counting Processes, and is editor of Scandinavian Journal of Statistics. Håkon K. Gjessing is professor of medical statistics at the Norwegian Institute of Public Health and the University of Bergen, Norway. Since his Ph.D. in probability in 1995, he has worked on a broad range of theoretical and applied problems in biostatistics | ||
| 650 | |a Ordres stochastiques | ||
| 650 | |a Distribution composée (théorie des probabilités) | ||
| 650 | |a Économétrie | ||
| 650 | |a Épidémiologie | ||
| 650 | |a Systèmes de sécurité | ||
| 650 | |a Analyse de survie (biométrie) | ||
| 700 | 1 | |a Borgan, Ørnulf, |d 1950- |4 aut | |
| 700 | 1 | |a Gjessing, Håkon K. |4 aut | |
| 776 | 0 | |0 127566287 |t Survival and event history analysis |o a process point of view |f by Odd Aalen, Ørnulf Borgan, Håkon K. Gjessing |d 2008 |c New York |n Springer |p 1 volume (XVIII-539 pages) |s Statistics for biology and health |z 978-0-387-20287-7 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/978-0-387-68560-1 |z Accès sur la plateforme de l'éditeur | |
| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-MJCHNW7T-W |z Accès sur la plateforme Istex | |
| 856 | 4 | |5 452349901:747857113 |u https://ezproxy.univ-orleans.fr/login?url=https://doi.org/10.1007/978-0-387-68560-1 |z Accès Université d'Orléans | |
| 856 | 4 | |5 180339901:750874589 |u https://ezproxy.insa-cvl.fr/login?qurl=https://doi.org/10.1007/978-0-387-68560-1 |z Accès INSA CVL | |
| 997 | |0 940753 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/Autre ressource numérique/ | ||