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Event History Analysis : a Process Point of View.
Demonstrates how counting processes, martingales, and stochastic integrals fit nicely with censored data. This book shows how dynamic path analyses can incorporate many modern causality ideas in a framework that takes the time aspect seriously. It includes examples from medicine. It is intended for...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Dordrecht :
Springer,
2008.
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| Colección: | Statistics for biology and health.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Survival and Event History Analysis; Preface; 1 An introduction to survival and event history analysis; 2 Stochastic processes in event history analysis; 3 Nonparametric analysis of survival and event history data; 4 Regression models; 5 Parametric counting process models; 6 Unobserved heterogeneity: The odd effects of frailty; 7 Multivariate frailty models; 8 Marginal and dynamic models for recurrent events and clustered survival data; 9 Causality; 10 First passage time models: Understanding the shape of the hazard rate; 11 Diffusion and Lévy process models for dynamic frailty.
- A Markov processes and the product-integralB Vector-valued counting processes, martingales and stochastic integrals; References; Author index; Index; com.